GPS World

Category: Opinions

  • Evolution: Machine learning for station specific Ionosphere prediction in GNSS positioning

    Evolution: Machine learning for station specific Ionosphere prediction in GNSS positioning

    Ionospheric delay remains a significant error source in GNSS positioning, particularly for single-frequency users and during periods of enhanced space weather activity (Dabbakuti, 2021). While global and regional ionospheric models provide large-scale corrections, they often fail to represent localized ionospheric variability at individual receiver locations (Jee et al., 2010; Osanyin et al, 2025).

    Consequently, residual ionospheric errors persist in positioning solutions, degrading accuracy for applications including precise point positioning (PPP), real-time navigation, and single-frequency GPS users (Biswas et al., 2022). Hence, accurate modeling of the ionosphere is essential in tackling the principal challenges in high-precision GNSS positioning. 

    Vertical total electron content (VTEC), a key driver of ionospheric delay, exhibits strong nonlinear temporal variability controlled by solar radiation, geomagnetic activity, seasonal effects, and local electrodynamics (Osanyin et al., 2023; Seemala et al., 2023). Capturing this variability at individual GNSS stations poses a significant challenge. Advances in artificial intelligence (AI), i.e., machine learning (ML) techniques have emerged over the decades as powerful tools for approximating complex non-linear systems and deterministic geophysical processes, while significantly reducing computational cost (Sarker, 2021). As such, they have successfully replaced repeated full-scale numerical simulations by learning input-output relationships directly from data (Zhang et al., 2025). This paradigm shift is particularly relevant for ionospheric modeling, where long-term GNSS observations provide rich time series well suited for data-driven learning.

    Time series forecasting traditionally relies on statistical models such as autoregressive (AR), moving average (MA), autoregressive moving average (ARMA), and autoregressive integrated moving average (ARIMA), which model future values as linear functions of past observations (Kaselimi et al., 2020). They have been widely employed to predict VTEC by extrapolating historical observations. Nonetheless, the classical approaches are inherently limited by assumptions of linearity, stationarity and short-term memory, which restrict their ability to capture complex ionospheric dynamics, particularly during disturbed conditions and over longer prediction horizons. To address these limitations, this study adopts a deep learning-based framework using long short-term memory (LSTM) neural networks for station -pecific VTEC prediction. Unlike conventional statistical models, LSTM networks are specifically designed to learn non-linear temporal relationships and retain long-term memory in sequential data (Hochreiter and Schmidhuber, 1997).

    Essentials

    LSTM neural networks for prediction have emerged as a powerful tool for time-series prediction (Hochreiter and Schmidhuber, 1997). LSTM is a type of recurrent neural networks (RNNs) that takes sequences of information and uses recurrent mechanisms and gate techniques (see Figure 1). RNNs are well known for their ability to process single data points and entire data sequences (Gonzalez and Yu, 2018). The LSTM model has various forms for different types of data inputs. The basic condition of LSTM modeling is that all inputs and outputs are independent of each other. The key to the LSTMs is the cell state, which is protected and controlled by the forget, input and output gates, respectively (Gonzalez and Yu, 2018).


    FIGURE 1  Comparison of recurrent neural network (RNN) and long short-term memory (LSTM) structures.

    Training deep learning models remains computationally demanding despite their fast prediction capability. LSTM networks consist of interconnected layers with numerous trainable parameters that must be optimized iteratively to accurately capture temporal dependencies in the data. Training typically involves large historical datasets spanning multiple years, which is necessary to expose the model to varying ionospheric conditions, but also increases computational effort (Thompson et al., 2020). The optimization process relies on iterative algorithms such as stochastic gradient descent and variants, requiring repeated forward and backward passes through the network. As the depth of the model and the length of input sequences increase, so does the demand for memory and processing power. These challenges are particularly relevant when training is performed using graphics processing units (GPUs), where memory limitations and data transfer overhead must be carefully managed (Sarker, 2021).

    Like all neural networks, LSTM has trainable parameters (weights and biases). These parameters are optimized by minimizing a loss function using gradient-based optimization. Due to its ability to learn time sequences, gradients must be propagated across time steps, not only across layers. This process is accomplished using backpropagation through time, which computes gradients of the loss with respect to all parameters and accumulates gradients across the sequence. The major advantage of LSTM is the use of its gating mechanism in mitigating vanishing gradients, making backpropagation practical for long time series such as VTEC (Adekunle et al., 2025; Hochreiter and Schmidhuber, 1997; Noor and Ige, 2025).

    In recent years, LSTM networks have achieved impressive results in modeling complex physical systems characterized by strong non-linearity and long-term temporal dependencies. Notably, LSTM-based approaches have been successfully applied to atmospheric and geophysical time series, demonstrating superiority in predictive skill compared to traditional empirical and statistical models (see Reddybattula et al. (2022 and references therein). These research results show the capability of LSTM to capture diurnal, seasonal, and storm-time variations. By leveraging historical GNSS-derived VTEC time series, LSTM-based models can adaptively capture both regular ionospheric patterns and transient disturbances, enabling more accurate and robust VTEC forecasts. This data-driven approach directly supports improved ionospheric correction in GNSS positioning, offering a practical and scalable solution to overcome the shortcomings of traditional time series methods. 

    This study focuses a station-specific vertical total electron content (VTEC) prediction framework based on long short-term time series. The proposed framework treats VTEC prediction as a supervised regression problem. A sequence of past VTEC observations is used to predict future values over one or multiple forecast horizons. Also, emphasis is placed on methodology clarity, practical implementation, and positioning relevance.

    Elements: TEC estimation from GNSS measurements

    For the purpose of forecasting local VTEC using time series analysis, this study utilized the GPS dataset provided by the Brazilian Institute for Geography and Statistics (RBGE; www.ibge.gov.br/en/) over Santa Maria (SMAR; -20.72o, 306.28o), a station located in Brazil over the period of 10 years from January 2010 to December 2019.

    VTEC data were derived from dual-frequency GPS observations at the selected station using the standard ionospheric processing techniques, including slant TEC estimation, instrumental bias correction, and mapping to vertical TEC. For more details, readers can consult the GPS-TEC analysis software developed by Seemala and Valladares (2011), which has been employed in this study for TEC processing. The time resolution is selected to be 15 minutes following an average over a sampling interval of 30 seconds. The resulting VTEC time series provides a continuous record of ionospheric variability with a fixed temporal resolution.

    Station-specific LSTM modeling framework

    A structured deep learning workflow for station-specific VTEC prediction has been adopted using the LSTM framework. The overall methodology follows a sequential pipeline consisting of data collection, preprocessing, feature engineering, model training, evaluation, validation, and deployment. This workflow ensures reproducibility, minimizes information leakage, and facilitates integration into GPS positioning engines. The focus is on time series learning at a single station, where temporal dependencies dominate and spatial smoothing from regional or global models is undesirable.

    Data preparation and model training

    High-quality input data are essential for stable LSTM training. The extracted VTEC time series are preprocessed to remove cycle slips, mitigate differential code biases, and ensure consistent temporal sampling. As shown in Figure 2, for this model (as variations can be considered), the dataset has been divided into training (80%), validation (10%), and testing (10%). The validation is mostly required during training the LSTM deep learning model to ensure generalization and prevent overfitting. Furthermore, preprocessing aims at ensuring capability of the model in handling missing data and temporal consistency checks.


    FIGURE 2  Chronological splitting of VTEC dataset for machine learning.

    Feature engineering mainly converts raw VTEC observations into structured model inputs such as local time (LT) and day-of-year (DOY) features. These features are normalized prior to training, although normalization is applicable to only the training dataset to avoid future leakage. The model consists of an input layer whose dimension equals the number of input features, followed by a single LSTM layer with 64 memory cells to learn temporal dependencies in the input sequence. A dropout layer with a rate of 0.2 is applied to mitigate overfitting during training. The LSTM representation is then passed to a fully connected (Dense) regression head with nout neurons, where nout  equals the number of forecast lead times. Model training minimizes the Huber loss function using gradient-based optimization, while performance is evaluated using RMSE. The optimizer updates the network weights iteratively to reduce the forecast error across the training samples. Early stopping and regularization are applied to further prevent overfitting, particularly during periods of low ionospheric variability. The final outputs are the predicted VTEC at multiple lead times (in this experiment: 30, 60, 120 and 180 minutes). The trained model is suitable for deployment in near real-time ionospheric correction systems: once operational, it ingests the most recent VTEC observations and produces short-term forecasts that can be integrated into GNSS positioning workflows, particularly for single-frequency applications and PPP.

    Performance evaluation and baseline comparison

    For practical assessment, the LSTM-based predictions are evaluated against commonly used baseline models, including persistence (using the trained model with new data) and skill (the ability of the model to make predictions). These baselines represent the minimum performance expected in operational GNSS ionospheric modeling and serves as internal validation of the overall model’s performance. Evaluation metrics include, but are not limited to, root mean square error (RMSE), mean absolute error (MAE), and relative improvement over persistence (skill). Figure 3 compares the predictive performance of the proposed LSTM model against the persistence baseline on the independent dataset. RMSE increases over time, while persistence largely deviates from the LSTM model, showing the great strength and capability of the LSTM model for time series prediction over the Santa Maria station. For instance, the RMSE of the LSTM model increases from 0.24 TECU to 1.15 TECU from 30 minutes to 3 hours lead time, while that of persistence ranges from 0.41 TECU to 2.25 TECU, respectively.  


    FIGURE 3  Comparison between the RMSE of the LSTM model and persistence for single-station VTEC prediction.

    For further evaluation, day-to-day variation of VTEC at 60 minutes lead time is shown in FIGURE 4. GPS TEC (orange curves) shows a strong diurnal cycle with expected daily peaks, while forecast (blue curves) matches these peaks across months, indicating that the LSTM captures the key deterministic component of TEC variability. TABLE  1 or the embedded metrics in Figure 4 summarizes an overall accuracy of the LSTM model using the performance metrics: MAE, RMSE, Bias, R, and skill. MAE and RMSE values change with season — with the lowest reported in July.


    FIGURE 4  Day-to-day variation of VTEC at 60 minutes forecast during July to December 2019. The embedded metrics show the performance of the LSTM model for each month of the testing dataset.

    Error increases toward December with the largest RMSE in March (0.549 TECU). September shows moderate error levels. Also, correlation is consistent across all months, which confirms the model’s capability to capture TEC changes and day-to-day variability patterns. The model is nearly unbiased as the bias is consistently close to zero, meaning that the LSTM does not drift systematically and shows that the model underpredicts GPS VTEC. This characteristic is important for operational GNSS corrections, because biased VTEC forecasts would translate to persistence positioning errors. Going by the skill values, even at 60 minutes forecast, the model provides ~27%-52% improvement over persistence. This result implies a major indicator of real predictive ability, especially for GNSS applications.

    Statistical validation

    Figure 5 presents the diagnostic of the validation dataset for the SMAR station at a 60-minute forecast horizon. It combines the distribution of prediction residuals (left) and density-based scatter comparison between predicted and observed VTEC values. These analyses help explain the overall agreement of the LSTM model forecast during validation.


    FIGURE 5  Validation diagnostics at 60 minutes forecast horizon. (Left) Histogram of prediction residuals. (Right) Density scatter of predicted versus observed TEC.

    The residual distribution is mostly concentrated near zero, which implies that most predictions deviate only slightly from observations. The right plot shows the scatter density plot of predicted VTEC against observed GPS VTEC. The points are tightly clustered along the dashed line, indicating that the model corresponds very well (98.2%) to the TEC variance in the validation period. Also, a RMSE of 0.39 TECU reflects a relatively low magnitude error. These findings support the reliability of the proposed LSTM model for VTEC forecasting.

    Implications for GNSS Positioning

    The cumulative distribution function (CDF) of the absolute equivalent L1 error, denoted by |∆ρ|, for the Santa Maria station at a forecast horizon of 60 minutes is shown in Figure 6.


    FIGURE 6  CDF of residual VTEC equivalent L1 ranging error at the single station.

    The CDF provides a direct positioning-relevant interpretation of model performance. The steep rise at small error values indicates that most samples exhibit low residual range errors, demonstrating strong correlation performance.

    Evolutionary

    This study demonstrates that LSTM-based machine learning provides a practical and effective approach for station-specific GNSS VTEC prediction during low solar activity. The LSTM model accurately reproduces diurnal and seasonal VTEC variability at the station level. Forecast skill remains stable across increasing horizons, while significant RMSE reductions over persistence confirm the model’s predictive value, supporting the feasibility of LSTM-based station-specific VTEC forecasting for operational GNSS applications. By leveraging historical GPS-derived VTEC time series, LSTM neural networks capture complex temporal dependencies that are difficult to model using conventional techniques. This approach offers a valuable complement to existing ionospheric correction models and represents a promising direction for future GNSS positioning systems. The results presented in Table 1 confirm that the proposed LSTM algorithm can derive an accurate predictive model as far as a 3-hour forecast. The proposed approach improves long-term ionospheric prediction and enhances positioning accuracy.

    MonthMAE (TECU)RMSE (TECU)Bias (TECU)RSkill
    Mar0.390.55-0.340.99344.5
    June0.150.18-0.120.99425.8
    Sep0.260.35-0.200.98628.0
    Dec0.360.49-0.280.99452.8

    Table 1  Comparison of VTEC performance metrics of the LSTM model at 60 minutes forecast.

    While the results demonstrate the potential of AI-based modeling for station-specific VTEC prediction, further investigation is required to assess its limitations. Future research will investigate the sensitivity and robustness of the data-driven approach under extreme geomagnetic storm conditions and maximum solar activity considering multiple stations over the same region. These experiments will help evaluate the LSTM-based modeling reliance for a better positioning GPS accuracy. In addition, combining efficient training strategies with LSTM-based temporal learning offers a practical and scalable solution to station-specific VTEC prediction. The resulting models will bridge the gap between computationally expensive physics-based approaches and overly simplified empirical models, providing accurate, localized ionospheric corrections that directly enhance GPS positioning performance. Therefore, the Bayesian optimization technique would be integrated during model’s training to tune LSTM hyperparameters (Adekunle et al., 2025), with the aim of reducing computational cost and improving convergence and generalization in station-specific ionospheric modeling. It is very likely that machine learning will play a significant role in near-term ionospheric modeling/prediction for GNSS. 

    Dr. Taiwo Osanyin is a Ph.D. visitor at York University, Toronto, Canada.  Her research interests include space physics, atmospheric sciences, statistics, and modeling of the upper atmosphere. Osanyin  received a Ph.D. in space geophysics from the National Institute for Space Research, Brazil, an M.Sc. in nuclear science and engineering from Obafemi Awolow University, Nigeria, and a B.Sc. in engineering physics from Obafemi Awolow University, Nigeria.

    Sunil Bisnath is a full professor in the Department of Earth and Space Science and Engineering at York University in Toronto. For more than 25 years, he has been actively researching precise GNSS-focused positioning and navigation solutions and applications. He holds an Honors Bachelor of Science degree and master of science degree in surveying science from the University of Toronto and a Ph.D. in geodesy and geomtics engineering from the University of New Brunswick.

    • Adekunle AA, Fofana I, Picher P, Rodriguez-Celis EM, Arroyo-Fernandez OH, Zemouri R. (2025). Optimizing deep learning predictive models: A comprehensive review of RNN and its variant architectures. Applied Soft Computing. Oct 9:114015.

    • Biswas T, Banerjee P and Paul A (2022). Impact of low-latitude ionospheric effects on precise position determination. Radio Science, 57(4): 1-11.

    • Dabbakuti JK (2021). Modeling and optimization of ionospheric model coefficients based on adjusted spherical harmonics function. Acta Astronautica, 182: 286-294.

    • Gonzalez J and Yu W (2018). Non-linear system modeling using LSTM neural networks. IFAC-PapersOnLine, 51(13): 485-489.

    • Hochreiter S and Schmidhuber J (1997). Long short-term memory. Neural Computation, 9:1735-1780.

    • Jee G, Lee HB, Kim YH, Chung JK, Cho J (2010). Assessment of GPS global ionosphere maps (GIM) by comparison between CODE GIM and TOPEX/Jason TEC data: Ionospheric perspective. Journal of Geophysical Research: Space Physics. 115: A10.

    • Kaselimi M, Voulodimos A, Doulamis N, Doulamis A, Delikaraoglou D. (2020). A causal long short-term memory sequence to sequence model for TEC prediction using GNSS observations. Remote Sensing. 12(9): 1354.

    • Noor MH and Ige AO (2025). A survey on state-of-the-art deep learning applications and challenges. Engineering Applications of Artificial Intelligence. 159: 111225.

    • Osanyin TO, Candido CM, Becker-Guedes F, Migoya-Orue Y, Habarulema JB, Obafaye AA, Chingarandi FS, Moraes-Santos SP (2023). Performance of a locally adapted NeQuick-2 model during high solar activity over the Brazilian equatorial and low-latitude region. Advances in Space Research. 72(12): 5520-38.

    • Osanyin TO, Maria Nicoli Candido C, Becker-Guedes F, Migoya-Orue Y, Habarulema JB (2025). Ingestion of GNSS-Derived-TEC Into NeQuick 2 Model Over South America. Space Weather. 23(12): e2024SW004212.

    • Reddybattula KD, Nelapudi LS, Moses M, Devanaboyina VR, Ali MA, Jamjareegulgarn P, Panda SK (2022). Ionospheric TEC forecasting over an Indian low latitude location using long short-term memory (LSTM) deep learning network. Universe. 8(11): 562.

    • Sarker IH (2021). Deep learning: a comprehensive overview on techniques, taxonomy, applications and research directions. SN Computer Science. 2(6): 1-20.

    • Seemala GK, Katual I, Kapil C, Vichare G (2023). Seasonal and solar activity dependence of TEC over Bharati station, Antarctica. Polar Science. 38: 101001.

    • Seemala GK, Valladares CE. Statistics of total electron content depletions observed over the South American continent for the year 2008 (2011). Radio Science. 46(05): 1-4.

    • Thompson Neil C, Kristjan G, Keeheon L, Manso Gabriel F (202). The computational limits of deep learning. Cornell University, arXiv:2007.05558, 10: 2.

    • Zhang R, Li H, Shen Y, Yang J, Li W, Zhao D, Hu A (2025). Deep learning applications in ionospheric modeling: progress, challenges, and opportunities. Remote Sensing. 17(1): 124.

  • UK’s Watchkeeper drone program nears the end: What went wrong and what’s to come

    UK’s Watchkeeper drone program nears the end: What went wrong and what’s to come

    We usually look for what’s new, with innovative drones emerging and gaining traction in commercial and military applications, but this month, news of the termination of a leading UAV program has sparked interest.

    The British Army’s Watchkeeper drone program has long been the subject of criticism over development delays, cost overruns and poor performance. Recent reports that the Watchkeeper fleet could be retired as early as 2025 — though that timeline may now slip to 2027 — have renewed scrutiny of the troubled effort. Perhaps a review of the story behind this drone adventure may be in order.

    The UK has been involved with drone operations going back into the 1960s, giving this military force deep experience and expertise in the field. Political support has enabled significant investment over time. When the Watchkeeper program was rolling in 2004-05, the US was moving toward the MQ-9 Reaper project, and military forces around the world were building their own mil-spec UAVs, mostly for surveillance to support military ground operations.

    At that time, few commercial drones existed beyond radio-controlled model aircraft flown by hobbyists. The idea was growing in China at that time for DJI and quad-copters, so these multi-use UAVs eventually emerged, and have led to a multitude of outfits elsewhere also making commercially available drones.

    When the Watchkeeper program took shape in 2004, developing a custom platform was essentially the only way for the UK to obtain a medium-altitude ISTAR intelligence, surveillance, target acquisition and reconnaissance (ISTAR) drone tailored to its requirements. The Ministry of Defence identified Israel-based Elbit Systems, which produced the Hermes 450 military drone, as a close match. The program was built around an extensively modified version of that aircraft, with the goal of bringing production to the UK

    Hermes 450 (Photo: Nehemia Gershuni-Aylho)
    Hermes 450 (Photo: Nehemia Gershuni-Aylho)
    Watchkeeper-X export version (Photo: U-tacS)
    Watchkeeper-X export version (Photo: U-tacS)

    In 2005, the U.K. Ministry of Defence awarded a £775 million contract to U-TacS, a joint venture between Thales UK and Elbit Systems, for the design, manufacture and support of 54 Watchkeeper WK-450 drones. The modifications involved making the UAV all-weather capable, including Thales integrated radar/GPS system for automated landing and take-off (Magic-ATOLS), Thales MASTER SAR/GMTI radar, dual electro-optical/IR cameras, laser designator, and tweaks to the Line-of-Sight radio system, with a satellite link option. Nevertheless, the range of the radio limits operation to within less than 100 miles of the mobile base-station, but it did provide a high-bandwidth, secure, direct, unobstructed wireless link for control and real-time video and targeting data back from the vehicle.

    Cost overruns and delays pushed the first flight to 2008 in Israel. Production of the WK-450 was then established at Thales UK, formerly Racal Electronics. The technology transfer between the two companies, separated by more than 2,000 miles, operating across different corporate cultures and exchanging proprietary material, proved more difficult and time-consuming than anticipated.

    The program delivered its first aircraft in 2014. Four drone systems flew in Afghanistan during the British troop withdrawal, logging a total of just 140 flight hours. Performance fell short of expectations, particularly the system’s all-weather capability, which proved inadequate in Afghan conditions. The U.S. military encountered similar challenges with sand contamination of helicopters and fixed-wing aircraft during early operations in Iraq and Afghanistan.

    As time rolled by, Watchkeeper found some use in Cyprus and in the UK, mostly for training, but problems continued. Between 2014 and 2022 eight vehicles crashed, and most have presumably been written off. Others have apparently experienced unplanned ‘contact with ground’ in more recent times. Faith in the now pretty old drone system has waned with the British forces — even recent political pressure to hand over the remaining fleet to Ukraine has been rebuffed by the Army — maybe too many problems with which to coach Ukraine troops. Watchkeeper is apparently now dismantled for the UK, along with the whole £1 billion investment. But not without gaining a lot of knowledge and operational experience, however an expensive lesson none the less.

    The UK has operated MQ-9A Reapers in Afghanistan, Iraq and Syria for more than 18 years, but after the Royal Air Force’s success with this US drone, these too have been retired in favor of the new MQ-9B Protector. The Protector has been customized and brought up to civilian certification standards by the manufacturer General Atomics. There have been similar sad programs with many ground, marine, and air projects around the world, but this has been such a visible and unhappy tale, it’s sad to see it end, but it’s probably a good thing so that other newer, more promising projects can get funding and become successful.

    Almost in the same breath, another UK company has already been supplying unmanned cargo aircraft to Ukrainian forces for more than three years. Windracer ULTRA is a twin-prop aircraft that can lift 330 lb for up to 620 miles, with 10 hours of endurance at a ceiling of up to 13,000ft. A newer version can reportedly travel twice as far with more payload.

    In Ukraine, the drone has been supplying front-line troop emplacements on a regular basis. The UK has been using ULTRA for surveillance and parachute drop re-supply, middle-mile parcel and cargo delivery to remote destinations, and for aerial surveys in Antarctica and elsewhere.

    So, a commercial start-up got there on its own, no direct government funding other than contracted support, and apparently no JV with another company!  So does 100% government funded development work better than setting up on your own, borrowing a bunch of cash, and doing it yourself? Mil-spec stuff is special with a limited market, so it’s unlikely that governments will ever be able to pick up finished products that fulfil all needs, but as the U.S. is proving with its bulk buy of off-the-shelf small one-way UAVs, these can meet many requirements.

  • FGCS meets to address the National Spatial Reference System

    FGCS meets to address the National Spatial Reference System

    In last month’s GPS World newsletter, I mentioned that the National Geodetic Survey (NGS) would host a meeting of federal geospatial agencies under the auspices of the Federal Geodetic Control Subcommittee (FGCS). The purpose is to increase awareness and coordinate the NSRS Modernization across the government.

    The FGCS meeting took place on Wednesday, Jan. 21, 2026. This session was highly informative and played a key role in aligning federal agency engagement strategies and self-assessments in preparation for the final adoption of the modernized NSRS and its associated new datums.

    The FGCS holds a central position within the Federal Geographic Data Committee (FGDC). It coordinates geodetic activities across the federal government by

    • Developing and promoting standards
    • Advancing the use of authoritative geodetic control
    • Facilitating the modernization of the NSRS across agencies
    • Recommending the official adoption of the modernized NSRS by the FGDC as the foundational basis for geodetic control throughout the United States.

    The agenda for the Jan. 21 meeting is detailed in the section titled “Federal Geodetic Control Subcommittee Meeting.” This gathering supported broader efforts to raise awareness, ensure coordination and prepare agencies for the upcoming transition to the modernized NSRS, with formal approval and release anticipated later in 2027.

    Federal Geodetic Control Subcommittee Meeting

    January 21, 2026

    Agenda: 

    MC: Christine Gallagher

    TimeTopicPresenter
    1:00 – 1:15 pmWelcome and IntroductionsDaniel Roman
    1:15 – 1:20 pmNational Geodetic Survey (NGS) UpdateMarian Westley
    1:20 – 1:30 pmGeodetic Control Theme Update and its Modernization TimelinesDaniel Roman
    1:30 – 2:00 pm NGS Modernization Engagement Plan and ProgressDana J Caccamise II / Christine Gallagher
    2:00 – 2:15 pmBureau of Ocean Energy Management / Kearns & WestAndy Archer / Kyle Vint
    2:15 – 2:30 pmUS Census National Spatial Reference System (NSRS) Modernization PreparationVince Ossier / Josh Coutts
    2:30 – 2:40 pmBreak
    2:40 – 2:55 pmUS Department of Transportation NSRS Modernization PreparationAmy Nelson / Derald Dudley
    2:55 – 3:10 pmAmerican Society for Photogrammetry and Remote Sensing & National Society of Professional Surveyors Working Groups Chris Parrish / Linda Foster
    3:10- 3:50 pmDiscussion: Q&A from Agency presentations. What hurdles to implementation do you see or anticipate? Share your insights from internal working groupsGroup Discussion Moderator:  Dana J Caccamise II and Daniel Roman
    3:50 – 4:00 pmClosing Remarks Daniel Roman
    Adjourn to Silver Branch

    The meeting lasted three hours and covered a lot of material. Below are highlights; contact FGCS for the full meeting recording.

    Christine Gallagher, NGS, opened the FGCS session and introduced Dan Roman, NOAA’s National Geodetic Survey senior advisor for geodesy.

    Roman welcomed everyone and briefly outlined the meeting’s purpose. He then introduced Marian Westley, director of the Center for Operational Oceanographic Products and Services (CO-OPS) and current acting director of NGS.

    Westley’s remarks were brief but important. She noted CO-OPS manages tide gauges and is updating several datums in partnership with NGS, including the Great Lakes International Great Lakes datum. She said the United States and Canada, along with NOS and other federal agencies such as the Corps of Engineers, are heavily involved in Great Lakes management. She also reported that CO-OPS is updating the National Tidal Datum Epoch (current NTDE: 1983-2001) and is working closely with NGS to tie the updated NTDE to the new NSRS. See the image titled “The NTDE Update: New Tidal Datums are Coming!“

    During Roman’s comments, he highlighted the agencies and professional societies participating in the meeting presentations and provided an update on the latest rollout schedule for the modernized NSRS.

    He emphasized that this Jan. 21, FGCS meeting marks the start of a broader coordination process. The primary purpose of this high-level session was to facilitate the sharing of experiences, strategies, and best practices among federal agencies as they prepare for NGS’s NSRS modernization and the transition to the new reference frames and datums.

    Roman noted that future FGCS meetings will shift to a more technical and detailed focus. These subsequent sessions will allow agencies to present their self-assessment results, outline implementation strategies, and discuss progress toward adopting the modernized NSRS.

    Key objectives across these meetings include:

    • Collecting questions and feedback from participants,
    • Understanding user needs and required accuracy levels,
    • Identifying anticipated challenges during the transition,
    • Exploring opportunities for federal agencies to collaborate and support one another throughout the implementation process.

    This series of FGCS engagements aims to ensure coordinated, informed, and effective preparation across the federal government ahead of the final adoption and full rollout of the modernized NSRS.

    Here are a few key points based on Dan’s remarks:

    • Today’s presentations provide a broad overview of geospatial data modernization to inform departments about actions they may need to take and to start a dialogue about what each department is doing.
    • NGS encourages agencies to form working groups; those groups must define their own requirements and create migration plans, including assessing existing data, required accuracies, and the tools needed based on product accuracy statements.  [Note: My October 2025 GPS World newsletter highlighted organizations that are forming 2022 Reference Working Groups.]  NGS will designate points of contact to facilitate discussions and planning.
    • FGCS provides guidance on using geodetic data with various tools, models, and SOPs. User needs vary by accuracy: e.g., a 3-meter horizontal allowance (aids to navigation) is straightforward, while 3-centimeter requirements (e.g., FEMA Elevation Certificate) need more precise methods.
    • Several beta products released in July 2025 are being finalized, enabling the private sector to integrate them into services.  NGS is currently developing models and software to transform coordinates from the old datum to the new one. These models are expected around March, and in June/July NGS anticipates releasing an updated Beta NCAT tool to transform coordinates to the new datum. This tool will help users understand differences in local datums.
    • Final steps include FGCS recommendations for FGDC to adopt the new NSRS and to publish a Federal Register notice on the adoption of the modernized NSRS, anticipated to be completed in early 2027.

    After Dan Roman’s comments, Dana J Caccamise II gave a presentation describing NGS Modernization Engagement Plan and Progress.  Dana should get an award for material he has prepared and for his work to assist agencies and professional organizations in preparing for the new NSRS.  In my October 2025 GPS World Survey Scene newsletter, I highlighted the work of Dana J. Caccamise II, NGS regional geodetic advisor. Dana has developed vital guidance materials shared with federal agencies — such as the Federal Geographic Data Committee (FGDC) and professional organizations including the National Society of Surveyors (NSPS), American Society of Photogrammetry and Remote Sensing (ASPRS), and American Association for Geodetic Surveying (AAGS). 

    Here are a few key points based on Dana’s presentation titled “Visualizing Impact: Preparing for NSRS Modernization Through Geospatial Readiness and Collaboration.”

    • Caccamise said that what started as a focused task quickly grew into a broader strategic effort. He shared insights to encourage thinking about NSRS modernization not merely as a technical update but as a strategic business decision that will shape how agencies create, manage, and share basic data across programs, systems, and partnerships.
    • Caccamise briefly provided details to the U.S. Census. Before diving into modernization, he offered a personal glimpse of what it’s like to do a federal detail across agencies, noting he was fortunate to do a detail with the Census not long ago.
    Image: FGCS January 21, 2026, Public Meeting
    Image: FGCS Jan. 21, 2026, Public Meeting
    • Drawing on his experience, Caccamise emphasized the importance of cross-agency readiness and of building resilient trust and communication structures. While on detail at the Census, he was regularly surprised by new challenges, which made the work engaging; he strongly recommended that others take a detail at another agency if they have the opportunity. A key takeaway was the value of visualizing impact: beyond cataloging geospatial datasets, users must identify which support critical decisions, which are shared across agencies, and which risk becoming outdated if you don’t adapt. Mapping themes and workflows revealed real dependencies and, more importantly, vulnerabilities. That detail shifted his  focus from “what data do we have” to “what roles does this data play.”
    Image: FGCS January 21, 2026, Public Meeting
    Image: FGCS Jan. 21, 2026, Public Meeting
    • Efforts around NSRS modernization include a key product developed by Caccamise: the Ready Package. Designed to help agencies assess their readiness for NSRS modernization, the package includes communication tools, technical checklists, and talking points to support agency staff.
    Image: FGCS January 21, 2026, Public Meeting
    Image: FGCS Jan. 21, 2026, Public Meeting
    • He mentioned that from field-level GIS technicians to senior policy leads, everyone needs to understand what’s changing and why it matters. A key part of engagement is meeting people where they are. Dana has worked with agency partners to raise awareness, build interest, and strengthen understanding — not just of technical changes but of the organizational shifts needed for a smooth transition.
    • For agencies whose statistical workflows depend on spatially referenced data, that means ensuring location-based datasets remain accurate, comparable over time, and interoperable across programs when the reference system changes. Ultimately, this is about more than new coordinates: it’s about linking strategic planning to operational implementation, from data collection and integration to interagency coordination and informed decision-making.
    • He mentioned that the big question he’s hearing from many organizations is: how should customers and partners prepare for modernization?   He provided the following advice.  Start by evaluating your geospatial workflows to understand how the transition will affect data management, operations, and decision-making. Assess dependencies on NGS products and services to ensure continued access and interoperability and proactively identify challenges and opportunities – he mentioned that NGS can’t do this for you because each agency’s situation is unique. Address potential impacts early to reduce operational risk by finding weak points before they cause surprises. Act now: preparing early will minimize future cost and complexity.
    Image: FGCS January 21, 2026, Public Meeting
    Image: FGCS Jan. 21, 2026, Public Meeting
    • For example, working with the Census under the current national spatial reference system highlights the geographic scope of some operational areas, which span multiple tectonic plates as modeled in the modernized NSRS. Even small regional differences can affect how location-based data are collected, integrated, and compared — especially for programs that need consistent, long-term geospatial baselines. Today, federal agencies commonly use three reference systems — NAD27, NAD83, and WGS84, which complicates geospatial data management.
    • The Census is a major user and producer of geospatial data, relying on GIS to support operations. This includes the MAF/TIGER geographic database, which contains roads, rail lines, hydrography, landmark features, and legal and statistical boundaries.
    • Along with many other critical datasets, the Census’s collaborative spatial and statistical research is more effective and interoperable when grounded in a common reference system, such as the National Spatial Reference System.
    Image: FGCS January 21, 2026, Public Meeting
    Image: FGCS Jan. 21, 2026, Public Meeting
    • Because these datasets are inherently geospatial, many, especially those requiring high positional accuracy or relying on external references such as airborne or satellite data, will be affected by NSRS modernization. The update will enable more consistent data stewardship and support integrated spatial analytics, helping align with individual agency spatial data strategies. Bureau-level geospatial work becomes more effective and future-ready when supported by a modern, shared spatial reference system like the NSRS.
    • One of the biggest risks is cultural, not technical. If the NSRS is treated as just another dataset, rather than an enabling framework, the foundation for other systems weakens. When the NSRS is recognized as the framework, everything built on it has a solid base. You can’t manage risk if you can’t measure it—and the NSRS is how we measure. Here are a few practical examples.
    • Floodplain mapping and storm surge models depend on accurate vertical data. Errors of even a foot can leave neighborhoods unprotected or cause unnecessary regulation.
    • In transportation, subsidence is a hidden risk: roads and bridges may seem fine until precise geometric monitoring reveals sinking.
    • Shoreline change is a growing challenge; coastal communities need accurate shoreline monitoring for planning and insurance.
    • In public safety, emergency response relies on precise locations — from 911 calls to field deployments. Seconds and meters matter when lives are on the line.
    Image: FGCS January 21, 2026, Public Meeting
    Image: FGCS Jan. 21, 2026, Public Meeting
    • As Roman mentioned, Caccamise also stated that the modernized NSRS is being released in phases. Initial beta releases are available now for testing and evaluation—not final production. NGS plans to release the remaining components in beta during this calendar year. The modernized NSRS will replace the current datums at least six months after the final preliminary component is released, giving partners time to review the beta and provide feedback. Near the end of this period, FGCS will convene to discuss and socialize the modernization details and the planned datum replacement.

    Next steps for your agency’s modernization:

    • Evaluate operational needs and identify changes that aren’t necessary.
    • Assess organizational impacts and staff readiness—are teams prepared for modernization?
    • Determine how existing programs and regional support will be affected.
    • Collaborate with partner agencies to align shared datasets, reduce redundancy, and maximize efficiency.
    • Prioritize leadership and communication to ensure the organization understands the changes.
    • Plan for future improvements in spatial accuracy, even if you don’t need them immediately.
    Image: FGCS January 21, 2026, Public Meeting
    Image: FGCS Jan. 21, 2026, Public Meeting
    • As noted by Dan Roman, Dana Caccamise also highlighted that many lower-accuracy datasets may not require coordinate changes beyond updating their metadata—typically those with spatial accuracy on the order of 10 ft or worse. However, he also noted an important caveat: many operational workflows don’t actively read or enforce metadata. In those cases, the risk is not the dataset itself but the accuracy context that becomes embedded as data moves through systems.
    • An early, critical step is therefore to identify not only which datasets are likely unaffected but also how those datasets are consumed, transformed, and reused. That approach prevents unnecessary work and avoids unintended downstream impacts. Remember: NSRS modernization is more than a technical update, it’s an opportunity to strengthen your agency’s future geospatial capabilities.
    • Now, I know this newsletter is long, but I would like to highlight one more presentation that I believe provides a model for other agencies to follow.  That is, the presentation of the Department of Interior’s Bureau of Ocean Energy Management (BOEM) activities presented by Kyle Vint (Vice President, Kearns & West) – “From Proactive Engagement to Lasting Impact: BOEM’s Path to Datum Readiness.” 
    Image: FGCS January 21, 2026, Public Meeting
    Image: FGCS Jan. 21, 2026, Public Meeting

    Kearns & West is a communications and engagement specialization firm.  The materials that they develop to support internal communications and outreach within an organization are available for other organizations. They provided a QR code for others to access their resources.

    Vint outlined BOEM’s operating context and described how the agency is proactively addressing NSRS modernization, including several strategies.

    Image: FGCS January 21, 2026, Meeting
    Image: FGCS Jan. 21, 2026, Meeting

    BOEM’s challenges are partly historical: until about 2010, it was part of a parent agency that has since split into three separate agencies. That fragmentation means BOEM must coordinate data and change management not only internally but across three agencies that share data centers and geospatial datasets. BOEM relies on authoritative geospatial data to manage offshore energy and mineral activities on the Outer Continental Shelf; BOEM’s Geospatial Services Division supports this by maintaining leases and boundaries that underpin program decision-making. Because the ocean serves many purposes, BOEM relies on multiple layers of information from different agencies to support those decisions.

    BOEM’s path to modernization is further complicated by internal organizational factors. The agency struggled with the NAD27-to-NAD83 transition due to resource constraints and misunderstandings — some staff believed modernization would alter legal lease blocks, which they expected to be immutable — so the transition was not fully implemented.

    Image: FGCS January 21, 2026, Meeting
    Image: FGCS January 21, 2026, Meeting

    BOEM holds large datasets in both NAD27 and NAD83, fragmenting its workflow. Maintaining and converting between multiple reference systems is labor-intensive and introduces inconsistencies.

    BOEM must dedicate substantial staff time to managing data in multiple reference systems. BOEM’s Geospatial Services Division recognized early that continuing workarounds would increase risk over time, so they began proactive modernization planning.

    The Geospatial Services Division saw this as more than a technical issue — it’s also a people, communication, and resourcing challenge. BOEM shifted from fragmented efforts to a proactive, multi‑year planning approach emphasizing governance, leadership buy‑in, and clear communication. The Geospatial Services Division established a milestone‑based approach for consistent messaging and coordination across stakeholders and offers internal expertise to support programs and regions as they assess costs and technical complexity.

    Their strategy seeks common ground to pool resources for shared problems and to use the Geospatial Services Division as an internal augmentation so individual offices aren’t forced to opt out. This reduces cost uncertainty and enables realistic planning for timelines and required participants.

    Image: FGCS January 21, 2026, Public Meeting
    Image: FGCS January 21, 2026, Public Meeting

    As part of the process, user personas were created to identify who would struggle with each step and who would benefit from early, sustained engagement. For each group, they defined the value of participating and explained why they were invited.

    BOEM leaderships were treated like investors—they ensured they brought geospatial experts to meetings so questions could be answered, and so leadership had actionable budget information for long‑term planning. At the program and regional level, data experts who know existing datasets, reference systems, dependent applications, and potential workflow challenges were part of the process.

    They also documented internal roles so others can model the approach. The Geospatial Services Division coordinates the effort across the organization. Program and regional experts provide domain knowledge. Kearns & West (technical and communications contractors) supported messaging, prepared materials, and ran meetings so BOEM staff could focus on the conversation. Clear roles and sustained engagement have been critical in this multi‑year planning effort.

    Image: FGCS January 21, 2026, Public Meeting
    Image: FGCS January 21, 2026, Public Meeting

    The team developed a Survey and sent it to each program and region to gather resource requirements. The survey asked what data they have and its characteristics, which applications or workflows depend on that data and could be affected by modernization, and what technical resources they expect will be needed to support budgeting.

    Image: FGCS January 21, 2026, Meeting
    Image: FGCS January 21, 2026, Meeting

    As part of the process, they are building internal champions to advocate for the effort, simplifying complex issues so staff can brief leadership, and convening agencies, partners, and industry to co-create solutions.

    Finally — thanks for sticking with this lengthy newsletter. I know it’s long, but the information is important for federal agencies and their contractors. One more item: a key session is scheduled for GeoWeek — “Roundtable – NSRS Modernization and Professional Societies” — on 02/18/2026 at 10:30 AM. See the box titled “Roundtable – NSRS Modernization and Professional Societies” for presentation and speaker details.

  • Communications-PNT integration: A new architectural layer for resilient and ubiquitous navigation

    Communications-PNT integration: A new architectural layer for resilient and ubiquitous navigation

    1. Introduction

    Throughout the past several decades, GNSS has become one of the most significant technologies in modern engineering, supporting transportation, communications, finance, emergency response, and critical infrastructure [1]. Its precision, global reach, and reliability have enabled entire industries to scale in ways that would otherwise have been impossible. Yet as GNSS is used more deeply in autonomy-driven and safety-critical domains, the limitations of relying on a single-layer PNT architecture are becoming increasingly apparent.

    Urban canyons degrade satellite geometry and tracking performance; intentional and unintentional interference is now commonplace [2]; spoofing has shifted from a theoretical concern to an operational reality; and indoor environments, which are essential for robotics, logistics, and emergency services, remain largely outside GNSS’s physical reach. These challenges are not shortcomings of GNSS itself. They reflect what the system was originally designed to provide: a globally available positioning and timing reference, not the entire resilience burden for every PNT-dependent application.

    In parallel, communications technologies have undergone rapid transformation. The evolution from LTE to 5G, and soon to 6G, has introduced wider bandwidths, massive MIMO antenna arrays, improved network synchronization, and dense deployment across urban and indoor environments [3]. At the same time, LEO broadband constellations have matured into powerful satellite infrastructures capable of delivering strong signals, rapid Doppler dynamics, and frequent visibility. Although these systems were built primarily for data connectivity, their physical characteristics naturally lend themselves to positioning and timing.

    Taken together, these developments point toward a new direction for resilient PNT: a multi-layer architecture in which GNSS serves as the global reference layer and is complemented by high-power, high-dynamics LEO satellites, terrestrial 5G/6G networks and Wi-Fi systems, and a suite of onboard sensors that provide short-term stability and dead-reckoning capability. Figure 1 illustrates this emerging architecture and highlights how each layer contributes specific observables, coverage strengths, and levels of robustness. The remainder of this article examines the physical foundations of communications-based PNT, the role of LEO as an augmentation space segment, the engineering challenges inherent in multi-source navigation, and the system-level architecture that is now taking shape to deliver resilient and ubiquitous PNT.

    Figure 1. Multi-layer architecture for resilient PNT. (All figures provided by author)
    Figure 1. Multi-layer architecture for resilient PNT. (All figures provided by the author)

    2. Rationale Behind Communications–PNT Integration

    2. 1 Growing Dependence on PNT and GNSS Vulnerability

    Nearly every sector of modern life depends on GNSS-based positioning and timing. As reliance grows, exposure to GNSS limitations grows with it. Dense urban environments create severe multipath and signal blockage; jamming and spoofing incidents are now regularly reported near conflict zones and busy ports [4]; and autonomy concepts in aviation and ground mobility increasingly assume reliable PNT even when GNSS performance is degraded or unavailable.

    GNSS will remain the global reference layer, but it was never intended to carry the full burden of these mission-critical demands on its own. A complementary set of technologies is needed, systems that continue to function in GNSS-challenged environments and provide redundancy when satellite signals are unavailable, corrupted, or intermittent.

    Error! Reference source not found. illustrates this challenge in a representative urban-canyon environment. Tall buildings restrict line-of-sight to GNSS satellites and generate strong multipath reflections, resulting in weak and unreliable signals (Figure 2a). By contrast, terrestrial networks such as 5G/6G and Wi-Fi maintain strong signal levels and robust geometry because their transmitters are embedded within the built environment, often only tens or hundreds of meters away (Figure 2b). This complementary coverage is a fundamental motivation for integrating communications signals into future PNT architectures.

    Figure 2. Comparison of GNSS and terrestrial network coverage in urban canyons.
    Figure 2. Comparison of GNSS and terrestrial network coverage in urban canyons.
    2.2 Communication Networks Have Quietly Become PNT-Capable

    Modern communication networks have evolved far beyond their original purpose of data transport [5]. Several physical-layer characteristics now make 5G, Wi-Fi 7, and future 6G systems surprisingly well suited to PNT:

    • Wideband signals. Wi-Fi 7 supports 320-MHz channels and 5G FR2 offers up to 400 MHz, with multi-GHz bandwidths anticipated for 6G [6]. Wider bandwidth directly improves time-of-arrival (ToA) precision. The ToA uncertainty can be approximated by:
    • Massive MIMO. Multi-element antenna arrays estimate angle-of-arrival (AoA) and angle-of-departure (AoD), effectively turning base stations into spatial sensors capable of separating line-of-sight from multipath.
    • Dense deployment. Unlike GNSS satellites, orbiting at roughly 20,000 km, terrestrial networks are woven directly into the environment. Small cells and access points provide excellent geometry in exactly the locations where GNSS performance is weakest, including city centers, campuses, factories, and warehouses.
    • High signal power. Terrestrial signals arrive at the receiver tens of decibels stronger than GNSS, improving indoor penetration, acquisition speed, and robustness to interference.

    These features were introduced to enhance connectivity, yet they collectively create an RF landscape that is inherently PNT-capable.

    2.3 The Rise of LEO Constellations as a Complementary Space Layer

    A third major driver behind communications-enabled PNT is the rapid proliferation of LEO satellite constellations. Broadband systems such as Starlink and OneWeb, together with several emerging PNT-dedicated LEO constellations, offer distinct advantages [7]:

    • Stronger received power. LEO satellites operate at altitudes of roughly 500–1,200 km, far closer than GNSS satellites at 20,000 km or higher, resulting in significantly stronger received signals.
    • Rapid Doppler dynamics. The relative motion of LEO satellites produces large, fast-varying Doppler shifts, which improve observability of user velocity and, over short intervals, position.
    • Large constellation sizes. Hundreds or thousands of satellites create rich geometry and frequent visibility, enhancing availability and resilience.

    Although many LEO systems were designed primarily for communications, their signals can already be exploited opportunistically for positioning and timing. Purpose-built LEO-PNT systems extend these capabilities by offering wideband navigation signals, multi-frequency operation, and security features intended specifically for resilient PNT [7].

    These characteristics make LEO a natural augmentation layer, strengthening GNSS performance and providing additional robustness in degraded, obstructed, or contested environments.

    3. Technical Foundations of Communications-Based PNT

    Modern communication and LEO satellite systems provide a diverse set of physical-layer measurements that can be fused with GNSS to create a resilient, multi-layer PNT solution. These observables go well beyond traditional GNSS code and carrier measurements and include Doppler, ranging, time-of-arrival, round-trip time, angle-of-arrival, angle-of-departure, and received signal strength. Figure 3 summarizes this heterogeneous measurement landscape and shows how each layer contributes distinct observables to the fusion engine.

    Figure 3. PNT measurement diversity across GNSS, LEO-PNT, and terrestrial networks.
    Figure 3. PNT measurement diversity across GNSS, LEO-PNT, and terrestrial networks.
    3.1 High-Resolution Ranging from Wideband Waveforms

    Ranging accuracy is fundamentally linked to signal bandwidth. GNSS signals typically occupy 1–20 MHz, whereas modern communication waveforms may span hundreds of megahertz. Wider bandwidth enables finer temporal resolution, allowing receivers to separate closely spaced multipath components and improve time-of-arrival (ToA) precision [6].

    In practice, Wi-Fi 7 and 5G FR2 waveforms can support sub-meter ranging in favorable conditions and substantially enhance relative positioning indoors and in dense urban environments. Techniques such as two-way ranging, cooperative localization, and inertial smoothing can extend performance even further. As shown in Error! Reference source not found., these wideband ToA and RTT observables form an essential input to the PNT measurement fusion layer.

    3.2 Spatial Sensing with Massive MIMO

    Massive MIMO arrays are one of the most powerful enablers of communications-based PNT. By comparing the phase and amplitude across many antenna elements, base stations estimate angles of arrival (AoA) and departure (AoD), turning terrestrial infrastructure into distributed RF sensor arrays [8].

    Angle-based measurements offer several important benefits:

    • Improved localization geometry in 3D urban canyons
    • Ability to distinguish line-of-sight (LOS) from multipath
    • High update rates suitable for UAVs and advanced air mobility (AAM) platforms

    A simplified Cramér–Rao lower bound (CRLB) illustrates how antenna geometry and signal power influence the accuracy of AoA estimation:

    3.3 Infrastructure Density and Geometric Strength

    From a PNT perspective, measurement geometry can be as important as measurement precision. Dense deployments of base stations, small cells, and access points give 5G, 6G, and Wi-Fi networks inherently strong geometric diversity, especially in environments where GNSS geometry collapses.

    In indoor settings or street canyons, a receiver may have ten or more RF sources within a few hundred meters. This density improves dilution of precision (DOP), increases redundancy, and enables fallback positioning even when GNSS availability drops to zero. Within the multi-layer architecture described in Figure 1, terrestrial networks therefore provide crucial observability in GNSS-restricted environments.

    3.4 High Signal Power and Robust Tracking

    Terrestrial and LEO communication signals enjoy a link-budget advantage of roughly 50–100 dB over GNSS. This additional power yields several practical benefits:

    • Better performance with small or non-ideal antennas
    • Increased resilience to interference and jamming
    • Faster acquisition and re-acquisition after outages
    • More reliable tracking under fast dynamics or partial obstruction

    In many scenarios, 5G, Wi-Fi, and LEO signals remain trackable long after GNSS signals fall below usable thresholds, providing essential continuity for navigation filters and multi-sensor fusion engines.

    3.5 Timing and Synchronization in Communication Networks

    Modern wireless networks rely on tight synchronization for scheduling, beamforming, and coordinated MIMO. They obtain timing from GNSS, fiber distribution, and packet-based protocols such as IEEE 1588 Precision Time Protocol (PTP) [9]. As these timing infrastructures mature, communication networks increasingly become timing providers rather than solely timing consumers.

    Although terrestrial networks do not yet match the long-term stability of GNSS-disciplined oscillators, they provide valuable short-term holdover and regional timing continuity. These capabilities play an important role in multi-layer PNT systems, particularly during GNSS outages.

    4. Engineering Challenges and Limitations

    Although communications-based PNT provides powerful complementary capabilities, significant engineering challenges remain. These challenges do not diminish the value of multi-layer PNT; rather, they highlight the technical rigor required to deploy these systems reliably on a scale.

    4.1 Multipath and Non-Line-of-Sight Propagation

    For terrestrial PNT, multipath and non-LOS propagation remain the dominant contributors to ranging and angle errors. Buildings, vehicles, reflective indoor structures, and metallic industrial environments introduce secondary paths that bias ToA, RTT, AoA, and Doppler measurements. A simplified model of multipath-induced ToA bias is:

    Massive MIMO beamforming, high-resolution channel estimation, and machine-learning LOS classifiers can mitigate these errors, but performance is highly environment-dependent and cannot be guaranteed in all cases. Figure 3, introduced earlier, highlights how diversity in measurement types helps reduce susceptibility to any single error mechanism.

    4.2 Synchronization Constraints and Timing Drift

    Communication networks require precise time alignment for scheduling, beamforming, and coordinated MIMO. However, network clocks do not yet match the long-term stability of GNSS-disciplined oscillators. Backhaul delay variability, oscillator drift, and partial GNSS visibility at base stations introduce timing uncertainty that must be explicitly modeled in a PNT fusion engine.

    Figure 4 illustrates timing error growth during a GNSS outage, comparing:

    • GNSS-only timing, which diverges quickly without satellite visibility
    • Network timing holdover, which slows but does not halt drift
    • Multi-layer timing fusion, which maintains the lowest error accumulation

    These behaviors demonstrate why communication-based timing is best used as a complementary layer rather than a standalone reference.

    Figure 4. Timing error comparison during a GNSS timing outage.

    4.3 Waveform and Structural Limitations

    Modern communication waveforms such as OFDM were optimized for throughput and spectral efficiency, not navigation. Several characteristics constrain raw positioning performance:

    • Finite pilot density limits effective ranging bandwidth
    • High peak-to-average power ratio (PAPR) stresses nonlinear receivers
    • Cyclic prefix duration restricts ToA resolution
    • TDD reciprocity assumptions introduce calibration-dependent biases

    4.4 Coverage Variability and Regulatory Constraints

    Terrestrial network density varies sharply by geography. Urban cores, industrial sites, and indoor campuses enjoy strong 5G/6G and Wi-Fi coverage, whereas rural, maritime, and mountainous regions may see limited improvements without LEO-PNT augmentation. Spectrum policy, privacy rules, and operator-controlled access to timing and positioning features further constrain how widely these capabilities can be exposed. Figure 5 summarizes the relative contribution of each PNT layer—GNSS, LEO-PNT, terrestrial networks, and onboard sensors—across open-sky, urban, and indoor environments.

    Figure 5. Relative contribution of PNT layers across operational environments.

    4.5 Security and integrity

    As communication signals begin supporting navigation functions, they must meet higher standards for robustness, integrity, and security. PNT observables are vulnerable to spoofing, replay, meaconing and cyber-attacks on timing sources [10]. GNSS experience demonstrates the value of:

    • Cross-layer consistency checks
    • Cryptographic authentication
    • Fault detection and exclusion (FDE)
    • Monitoring for anomalies in Doppler, timing, or angle domains
    • Redundancy across multiple constellations and layers.

    These functions are visualized in Figure 6, which illustrates how a multi-layer PNT system performs integrity monitoring across heterogeneous measurements.

    5. A Multi-Layer Architecture for Future PNT

    The earlier sections described why GNSS alone cannot meet emerging PNT requirements and how communications and LEO signals provide new sources of observability. Building on those foundations, Figure 1 introduces a multi-layer architecture in which GNSS, LEO-PNT, terrestrial networks, and onboard sensors cooperate to deliver resilient positioning and timing. This section outlines the role of each layer and how they integrate into a unified system.

    5.1 GNSS as the Foundational Global Layer

    GNSS will continue to provide the global reference frame, absolute positioning, and precise timing that anchor the entire architecture. Its worldwide availability, mature error modeling, and extensive user base make it the natural reference for other layers to align with whenever GNSS is available and reliable. In this sense, GNSS remains the “truth model” for time and coordinates, even as additional layers enhance resilience.

    5.2 LEO-PNT as the High-Power, High-Dynamics Space Layer

    LEO satellites provide diversity in orbit, signal power, geometry, and dynamics. Their lower altitude results in significantly stronger signals and rapid Doppler variations that improve motion observability. These characteristics reinforce GNSS performance in interference, urban canyon, and high-dynamics environments. As shown in Figure 3, LEO adds Doppler-based range-rate observables that are particularly valuable for maintaining continuity when GNSS quality fluctuates.

    5.3 Terrestrial Networks as the Urban and Indoor Layer

    5G, Wi-Fi 7, and future 6G networks form the densest PNT-capable infrastructure ever deployed. Their wideband signals, massive MIMO arrays, and strong received power position them as the dominant layer for indoor and urban navigation. Where GNSS geometry collapses, terrestrial networks provide ToA, AoA, AoD, RTT, and coverage exactly where users most often need it. Figure 5 highlights how their contribution becomes primary indoors and highly complementary in urban canyons.

    5.4 Onboard Sensors and Local References

    IMUs, odometry, barometers, cameras, radar, and lidar provide short-term stability and immediate awareness of the immediate environment, independent of external RF conditions. These sensors bridge outages and reduce reliance on any single external signal source. Their role within architecture mirrors their role in autonomy today: providing the continuity needed when GNSS, LEO, or terrestrial signals fluctuate. Together with RF observables, they form a robust solution space consistent with the measurement diversity shown in Figure 3.

    5.5 Fusion, Standards, and System Engineering

    Realizing a multi-layer PNT system is fundamentally a system-engineering effort. Success depends on:

    • Common timing and reference frameworks across GNSS, LEO, and terrestrial layers
    • Standardized quality indicators and integrity metrics
    • Interfaces that expose PNT-relevant observables from communication networks while respecting privacy and operational constraints
    • Cross-layer consistency checks that ensure no single measurement dominates unchecked

    Standards bodies, including 3GPP, IEEE and aviation authorities, are beginning to address these needs, but operationalizing multi-layer PNT at scale will require continued collaboration across industries. Figure 6 illustrates how integrity information from each layer contributes to fault detection, cross-checking, and integrity-bound estimation within the fusion engine.

    Figure 6. Integrity monitoring in multi-layer PNT architecture.
    Figure 6. Integrity monitoring in multi-layer PNT architecture.

    6. Conclusion

    The era of single-layer PNT is coming to an end. As reliance on precise positioning and timing accelerates across aviation, ground autonomy, critical infrastructure, and networked systems, GNSS alone cannot shoulder the growing resilience burden. Fortunately, a rich set of complementary technologies already surrounds us. Dense terrestrial networks, emerging LEO constellations, and increasingly capable onboard sensors provide observables that naturally augment GNSS and extend PNT into environments where satellite signals struggle.

    The opportunity now is to treat communications and PNT not as separate domains but as elements of a unified system. A multi-layer architecture — such as the one outlined in this article — offers stronger availability, improved measurement diversity, and inherent resilience against interference, outages, and environmental constraints. The key challenge ahead lies not in inventing new signals, but in system engineering: establishing shared timing frameworks, standardizing measurement interfaces, ensuring integrity across heterogeneous sources, and building trust in signals not originally designed for navigation.

    Most of the technical ingredients are already in place. The next decade will determine how effectively industry, government, research institutions, and standards bodies can integrate them into certifiable, interoperable, and widely deployable solutions. If successful, multi-layer PNT will become a foundational capability — providing trustworthy positioning and timing wherever future autonomous systems, vehicles, and critical infrastructure require it.

  • RQ-170 stealth drones tied to Venezuela operation as FCC bans foreign UAV imports

    RQ-170 stealth drones tied to Venezuela operation as FCC bans foreign UAV imports

    As the news subsides on the U.S. operation in Venezuela to capture Nicolás Maduro and his wife, attention is now turning to the legal aspects of the prosecution. Nevertheless, this military undertaking was apparently extremely complex and involved very discreet initial persistent surveillance of not only Maduro’s location but also of a large number of military installations and facilities.

    Venezuela has acquired an extensive arsenal of sophisticated Russian air defense capabilities beginning in 2011 and which were apparently recently upgraded in 2024. Heavy damage during the U.S. operation at La Carlota Air Base in Caracas, Fort Tiuna Military Complex, La Guaira Port and El Higuerote Airport appears to have overcome not only surface-to-air anti-aircraft missile systems but also Su-30 Sukhoi Flanker fighter aircraft armed with air-to-air missiles.

    And how was this accomplished? Well, likely with the help of legendary Lockheed RQ-170 Sentinel Stealth Drones. Nothing in the classified operation has been positively confirmed, but it is known that one or two of these surveillance drones were videoed returning to Naval Station Roosevelt Roads in Puerto Rico in the early morning of Jan. 3 following the U.S. attack. And piecing together earlier photos of U.S. Latin American command with an RQ-170 operations operative, pundits now believe confirm RQ-170 involvement.

    Lockheed RQ-170 stealth drone, nicknamed Wraith (Photo: USAF)
    Lockheed RQ-170 stealth drone, nicknamed Wraith (Photo: USAF)

    The 30th and 44th Reconnaissance Squadrons at Wing at Creech Air Force Base in Nevada are the only units the Air Force has confirmed to be operating RQ-170s Wraith low-observable stealth drones.

    It’s therefore quite possible that when President Trump said, “I was able to watch it in real time, and I watched every aspect of it,” that the video link may have been supplied by one or more of the RQ-170 Wraith drones circling over the action on the ground.

    Another aspect of the Venezuelan operation comes from people on the ground in Caracas who reported a number of instances of “flying bombs” which fell on targets during the U.S. operation. Video clips and numerous personal accounts apparently supported the reports that prop-powered attack drones were being crashed into ground targets, followed by big explosions.

    And previously on Dec. 16, the U.S. had a “first” for the U.S. Navy to have launched a one-way attack drone from the deck of the USS Santa Barbara in the Arabian Gulf. These earlier reports indicated that these attack drones could be launched by catapult, using rocket assist and from mobile ground vehicles.

    Therefore, it is not much of a leap to say it’s very likely that other marine and ground launch facilities in and around Venezuela dispatched many one-way, likely semi-autonomous attack-drones to take out targets prior to Delta Force being helicoptered in to capture Madura.

    Meanwhile back in the U.S., well away from military action, the Federal Communications Commission has effectively banned the sale of any new UAS or parts for UAS being imported into the U.S. The ruling was developed after the White House initiated a review aimed at protecting American security which decided “that UAS and UAS critical component parts that are produced in foreign countries pose unacceptable risks to the national security of the United States and to the safety and security of U.S. persons.”

    To somewhat clarify the situation, the FCC just added exemptions for Pentagon-approved “Blue List” drone models and parts thereof from EagleNXT, Parrot, Teledyne FLIR, Neros Technologies, Wingtra, Auterion, ModalAI, Zepher Flight Labs and AeroVironment — imports from these suppliers will be allowed through the end of 2026.

    So with new models of foreign drones being prevented from entering the U.S., the U.S. drone industry has been granted, at least for the moment, an opportunity to develop leading UAS models which will eventually outpace existing foreign drones operating in the U.S. It’s predicted that the FIFA soccer World Cup this summer will need a lot of drone coverage for security purposes — possibly a new U.S. drone home market.

    The Bell-Boeing V-22 Osprey is a complex military tilt-rotor aircraft which overcame many hurdles in its development and initial operations phase, even having some incidents during its mature field operations.

    Bell-Boeing V-22 Tilt-rotor aircraft (Photo: Boeing)
    Bell-Boeing V-22 Tilt-rotor aircraft (Photo: Boeing)

    Nevertheless, the Chinese appear to have adopted a similar design approach for the Lanying R-6000 manned/unmanned tilt-rotor 6-12 passenger eVTOL and a 2-ton-cargo transport version. The promotional video for the Chinese United Aircraft R-6000 seems to interchange shots of the V-22 in hover mode with recent R-6000 prototype system in hover flight. However, Bell-Boeing web statements disclaim any linkage with the Chinese company or its R-6000 development.

    If the name “United Aircraft” seems familiar, it’s because there was such a company in the U.S. in the 1930s, changing its name to United Technologies (Pratt & Whitney) in 1975, now RTX Corp.

    United Aircraft in China has apparently been around since 2012 and has produced a number of vertical lift aircraft, including the TD220 twin-coaxial helicopter (without tail boom). As with most large industrial companies in China, this one also seems heavily engaged with the Chinese military and is now making inroads into the civilian marketplace with a number of UAVs for various applications, leading up to the projected 550 mph Lanying R-6000, which has been depicted in low-level flight mode.

    Promotional image of eVTOL Lanying R-6000. (Photo: United Aircraft)
    Promotional image of eVTOL Lanying R-6000. (Photo: United Aircraft)

    So, a mixed bag of unmanned aircraft reports this month, ranging from drones likely used in the recent U.S. action in Venezuela, FCC rulemaking to restrict imports of foreign UAVs into the U.S., and all the way to a new potential Chinese tilt-rotor eVTOL entrant.

  • A New Year’s resolution for National Spatial Reference System users

    A New Year’s resolution for National Spatial Reference System users

    Happy New Year! I’ve always felt that a fresh calendar represents a world of new opportunities, and I wish you all a fantastic 2026. For many, this is a season for reflection and self-improvement, with goals typically centered on fitness, faith, personal growth or career milestones.

    As regular readers of this newsletter know, my primary focus over the past year has been to champion the importance of geodesy and to prepare the geospatial community for the National Geodetic Survey’s modernized National Spatial Reference System (NSRS).

    To see how modern tech would handle such a specialized professional niche, I asked the AI chatbot Grok: “What would be a good New Year’s resolution for a user of the National Spatial Reference System?”

    The response was quite insightful. Take a look at what it suggested below.

    What would be a good New Year’s Resolution for a user of the National Spatial Reference System? (Grok’s Response)

    Fun and Practical New Year’s Resolutions for NSRS Users

    As we head into 2026, the modernization of the NSRS is in full swing. NOAA’s National Geodetic Survey (NGS) released the first beta products in June 2025, with ongoing rollouts and testing throughout the year. The full transition to new frames like NATRF2022 and NAPGD2022 is expected soon, bringing centimeter-level accuracy aligned with GNSS and global standards—but it requires preparation.

    Here are some timely, geodesy-inspired New Year’s resolutions tailored for surveyors, GIS professionals, engineers, and anyone relying on the NSRS:

    1. Fully transition workflows to the modernized NSRS. Commit to updating software, processes, and datasets for the new terrestrial reference frames and geopotential datum. Test tools on the NGS Beta site and provide feedback to help shape the final rollout.

    esri.com

    gpsworld.com

    1. Achieve new heights (and accuracies) in 2026. Embrace NAPGD2022 for more precise orthometric heights. Resolve to reprocess key projects with updated transformations (via NCAT or VDatum) and say goodbye to NAVD 88 quirks.
    1. Stay grounded in best practices. Incorporate the latest NGS guidelines, like NOS NGS 92 standards for GNSS surveys. Attend webinars and workshops, or review resources, to keep your positioning sharp.

    gpsworld.com

    1. Contribute to the system. Submit high-quality GNSS data via OPUS-Share or participate in crowdsourced efforts to improve the network. Help make the NSRS even more robust for everyone.
    1. Measure progress monthly. Track how the modernization impacts your work—review coordinate shifts, audit legacy data, and plan for smoother integrations in future projects.

    These resolutions blend practicality with the spirit of improvement that defines geodesy. Happy New Year—may your positions be accurate, your elevations precise, and your datums forever modernized! For the latest updates, check geodesy.noaa.gov.

    It’s no surprise that Grok highlighted the NSRS modernization; it even incorporated a photo of a geodetic benchmark I took for my July 2025 GPS World Survey Scene newsletter.

    Understanding that most AI chatbots personalize results using past interactions (unless disabled), I wanted to test this. After clearing my cache and deleting all previous Grok interactions, I posed the question again.

    You can find that second, impersonalized response below.

    Second Response from Grok

    What would be a good New Year’s Resolution for a user of the National Spatial Reference System? Grok’s Second answer.

    Here are some practical, realistic, and useful New Year’s resolutions tailored for someone who regularly works with the NSRS whether you’re a surveyor, GIS professional, geodesist, engineer or data manager:

    1. “This year, I will stop mixing epochs without documenting them.” Resolve to always record the reference epoch (e.g., 2010.0, 2020.00) when I use NAD83(2011), NAD83(CORS96), NAD83(2011) epoch-specific coordinates, or when I transform to ITRF2020/2020.0. Bonus: add epoch to layer names and metadata.
    2. “I will run OPUS or CSRS-PPP at least once a month to keep my local control fresh.” Make it a habit to periodically re-observe a trusted point and submit it to NOAA’s OPUS (or CSRS-PPP in Canada) to verify that my local network hasn’t drifted too far from the national datum.
    3. “I will finally transition at least one active project to the modern NSRS (NAD83(2011)/NAVD88 → NATRF2022 / NAPGD2022).” Pick one ongoing or new project and do the full datum shift. Learn the tools (NADCON5, VERTCON3, GEOID18 → GEOID2022) and document what changed.
    4. “I will replace every ‘NAD83’ label that doesn’t specify an epoch or realization with something more precise.” No more generic “NAD83” in reports, plats, or metadata. Aim for “NAD83(2011) epoch 2010.0” or “NAD83(2011) CORS-derived” — or better yet, start using NATRF2022 when appropriate.
    5. “I will learn to use the NGS Coordinate Conversion and Transformation Tool (NCAT) fluently.” Commit to doing at least 5 conversions or transformations per month in NCAT instead of relying on old software or hand-calculated factors.
    6. “I will check the NGS Data Explorer / Datasheet for every benchmark or CORS I plan to use — before I use it.” No more assuming a published value is still good. Make it a 2-minute ritual to look up the latest adjusted position and velocity.
    7. “I will attend at least one NGS webinar or read one Bluebook chapter in 2026.” The NGS webinar series is free and excellent. Pick one session (e.g., on GEOID2022, NATRF2022 implementation, or GNSS vector processing) and actually watch it.
    8. “I will prepare a small ‘before/after’ datum comparison report for my organization or clients.” Quantify what the 2022–2025 NSRS modernization means in your typical project area (horizontal shift, orthometric height change). Even a one-page summary builds understanding and credibility.
    9. “I will stop treating GEOID18 as the final word and start using GEOID2022 for new work.” Especially important for projects that will live past 2025, as NGS is phasing out support for older geoids.

    Pick one or two that feel achievable and most relevant to your day-to-day work. My personal favorite starter resolution for most NSRS users in 2026: “In 2026, I will clearly label the datum, realization, epoch, and geoid model on every deliverable I produce.”

    That one habit alone dramatically reduces confusion downstream.

    I really appreciate Grok’s responses because they address crucial issues that many geospatial users either overlook or take for granted, emphasizing the importance of proper documentation and associated metadata.

    Key Resolution Examples:

    • Specificity: “I will replace every ‘NAD83’ label that doesn’t specify an epoch or realization with something more precise.”
    • Verification: “I will check the NGS Data Explorer / Datasheet for every benchmark or CORS I plan to use — before I use it.”

    It is important to note that the AI chatbot assumes the modernized NSRS has already been adopted, which, as of January 2026, is not the case. This highlights that AI still has limitations and requires human oversight.

    I challenge you to ask your own AI chatbot a similar, niche question related to your profession and compare its responses.

    Beyond the specific technical corrections, Grok provided excellent general advice for any geospatial professional. Take, for example, action items 1 and 5 from its first response:

    • Transition Workflows: Commit to fully updating software, processes, and datasets to align with the new terrestrial reference frames and geopotential datum.
    • Measure Progress Monthly: Track the real-world impact of modernization by reviewing coordinate shifts, auditing legacy data, and planning for smoother integrations in upcoming projects.

    Even though the modernized NSRS has not yet been officially adopted as of January 2026—with official release and FGCS approval expected later this year—following these steps now ensures you are prepared for the official transition when it occurs.

    So, how do we put this advice into action? In my October 2025 GPS World Survey Scene newsletter, I highlighted the work of Dana J. Caccamise II, NGS regional geodetic advisor. Dana has developed vital guidance materials shared with federal agencies—such as the Federal Geographic Data Committee (FGDC) and professional organizations including National Society of Surveyors (NSPS), American Society of Photogrammetry and Remote Sensing (ASPRS), and American Association for Geodetic Surveying (AAGS). 

    To help your team prepare for the official transition later this year, I’ve included a box titled “Questions to Guide a Self-Assessment of Your Operation and Products.” These questions, originally featured in my October newsletter, are designed to ensure your organization is fully equipped to implement the new NSRS the moment it is adopted.

    Questions to Guide a Self-Assessment of Your Operation and Products

    1. Are you generating or using geospatial data (or doing both)?
      • If so, your workflows are likely dependent on geodetic control tied to one or more NGS products. The upcoming NSRS update will affect these dependencies. (See the box titled “List of NGS Products and Services.”)
    2. Do you know if your mission, project, or datasets depend on NGS products?
      • Identifying whether and how your entity relies on NGS products is a critical first step in assessing potential impacts.
    3. What are your accuracy, precision, and shelf-life requirements for geospatial data?
      • Understanding your mission’s specific data requirements ensures you can evaluate whether NSRS modernization will meet your operational needs without unnecessary adjustments.  This should include plans to accommodate greater accuracy in the future.
    4. Do you know how your entity accesses and utilizes geospatial data?
      • Are you obtaining it directly from NGS or indirectly through third-party vendors (e.g., RTN systems, GIS platforms, GNSS companies)?
      • Many entities rely on geodetic control without realizing it. NGS’s foundational data and frameworks are often invisible and seamlessly embedded within the tools and services offered by third-party vendors, such as GIS platforms, survey equipment, and software providers. These vendors, in turn, depend heavily on NGS products like the NSRS to ensure their tools are accurate and functional. Understanding this indirect reliance is crucial for preparing your workflows and ensuring continuity as the NSRS is modernized.
    5. Where does your entity fit in with the geodetic workflow?
      • Does your entity create integral products (e.g., GNSS data, Lidar data) on which other products depend?
      • Evaluating these dependencies will help you determine the scope of NSRS modernization impacts.
    6. What are your project requirements for data accuracy and longevity?
      • Assess whether your data accuracy thresholds and long-term usability align with the modernized NSRS.
    7. Have you evaluated workflows and identified potential impacts in areas affected by significant ground movement (e.g., regions with tectonic shifts, vertical land motion, and, most notably, subsidence) 
      • Identifying potential risk or disruption areas can guide prioritization and help mitigate impacts on critical operations.

    In my October 2025 GPS World newsletter, I mentioned that the National Geodetic Survey (NGS) would be hosting a meeting with Federal geospatial agencies under the auspices of the Federal Geodetic Control Subcommittee (FGCS). The purpose is to increase awareness and coordinate the NSRS Modernization across the government.

    While the original meeting scheduled for October 15, 2025, was canceled due to the Federal Government Shutdown, it has been officially rescheduled for Wednesday, January 21, 2026. This meeting will be critical for aligning agency engagement strategies and self-assessments ahead of the final adoption of the new datums.

    As stated in my October 2025 newsletter, the primary objectives of this meeting are to:

    • Increase awareness of the National Spatial Reference System (NSRS) Modernization rollout schedule and engagement strategy, including self-assessment and interaction between official departmental working groups and an NGS point of contact.
    • Within other Departments, connect decision-makers to those who accomplish NSRS modernization tasks and designate points of contact to interface with NGS capacity-building efforts.
    • Share experiences and strategies among federal agencies concerning NSRS Modernization self-assessment and preparation.
    • (New) Formally transition the foundational beta products (released in May 2025) from preliminary to final.
    • Gather questions, discuss anticipated challenges, and identify opportunities to support each other through this transition.

    The FGCS plays a central role in coordinating geodetic activities across the federal government, including the development of standards and the promotion of the use of authoritative geodetic control (e.g., CORS, geoids) to ensure that geospatial data is accurate, accessible, and interoperable, and to advance the modernization of NSRS across agencies and recommend the adoption of the modernized NSRS by FGDC as the official basis for geodetic control in the United States. It is my understanding that this meeting is open to the public (virtually) for listening and observation.  The box titled “Federal Geodetic Control Subcommittee Meeting” provides the agenda of the January 21, 2026, meeting.

    Federal Geodetic Control Subcommittee Meeting Agenda held January 21, 2026.
    Federal Geodetic Control Subcommittee Meeting Agenda held January 21, 2026.

    To join the meeting virtually, registration is required. You can find all the necessary details and a direct link to sign up in the box titled “Registration for the Virtual Attendance of the Meeting.”

    Registration for the Virtual Attendance of the Meeting

    NOAA’s National Geodetic Survey (NGS) invites you to the upcoming Federal Geographic Data Committee (FGDC) Federal Geodetic Control Subcommittee (FGCS) meeting.

    • Date: Wednesday, January 21, 2026
    • Time: 1:00 PM – 4:00 PM ET
    • Location: Hybrid meeting, offering both in-person attendance at NOAA Offices in Silver Spring, MD, and virtual participation via WebEx.
      • If you plan to attend in person, please email [email protected] so we can ensure building access.

    If you plan to attend virtually, here is the registration link: https://ngs-nos-noaa.webex.com/weblink/register/r53ab4d202de3bb20df12d9364862ff0f

    As I mentioned in my October 2025 GPS World Survey Scene newsletter, several organizations have formed working groups to address the new NSRS. The National Society of Surveyors (NSPS) has released a story map to inform the professional surveying community and is developing guidance and case studies. The American Association for Geodetic Surveying (AAGS) is collaborating with NSPS. The American Society of Photogrammetry and Remote Sensing (ASPRS) has prepared materials available on its website.

    In October 2025, NSPS held its Fall meeting.  The box titled “Excerpts from 2025 NSPS Fall Meeting Report: October 17, 2025” contains excerpts from the report provided by Richard Kleinmann, Wisconsin NSPS Director, on the working group’s activities being performed by the National Society of Professional Surveyors (NSPS) Professional Standards NSRS Modernization Subcommittee.

    Excerpts from 2025 NSPS Fall Meeting Report: October 17, 2025

    Submitted by: Richard Kleinmann PLS, Wisconsin NSPS Director

    Subcommittee Purpose: To promote awareness, adoption, and readiness for the implementation of the Modernized National Spatial Reference System (NSRS) in cooperation with the National Geodetic Survey (NGS) and other geospatial groups.

    Activities: NSPS leadership and the NSRS Modernization Subcommittee continue to work closely with NGS to promote awareness, adoption, and readiness for the new 2022 datums, which are expected to be approved sometime in 2026. Due to federal funding challenges occurring in 2025, NSPS felt it necessary to intensify its support of NGS and the modernization of the NSRS which was the genesis of this subcommittee.

    As an outgrowth of interactions between NSPS & NGS during NGS quarterly meetings and at geospatial events such as the ESRI User Conference and Geo Week, the NSPS leadership team, and subsequently the NSRS Modernization Subcommittee, began developing a suite of resources — including an ArcGIS StoryMap with several resources useful for the transition.   See the link for the NSPS ArcGIS Story map here: https://share.google/oOAIapPQnux5q8nwl

    The NSRS Modernization Subcommittee is also working on a series of documents originally developed by Dana J. Caccamise of NGS intended to be used by Federal Agencies in the transition to the new datums.  We are adapting the documents to change the “voice” from NGS to NSPS and the intended audience to state, regional, county and local agencies, as well as private practitioners, to help them transition smoothly to the modernized NSRS.  At this point, the document package includes:

    • Initial outreach tools (Email & Leadership Memo), 
    • Technical readiness resources (Self-Assessment Checklist & Survey)
    • Briefing materials for agency coordination (Presentation Template)

    These document resources are being developed with the hope to share them via NSPS social media outreach efforts and possibly a geospatial information “hub” shared by NSPS and other geospatial organizations.

    Proposed Whitepapers/Use Case Reports: The intent of these whitepapers is to is to provide a somewhat higher-level view of how the transition to the new datums/frames can be accomplished by showing what tools are available and what to consider when designing a project approach.  Our hope is to promote the adoption of the new datums and share the benefits of doing so.  Basically, adopting a “be prepared, not scared” attitude.  We are looking for people willing to share their solutions so others can benefit from their experience and be more likely to be early adopters.  It is not our intent to develop detailed step by step recipes that can be blindly followed because every geographic region has their unique circumstances that need to be considered but the white papers will instead supply the foundation for them to confidently build a project approach that works in their situation.

    Coordination with other working groups: NSPS is looking forward to coordinating with similar Working Groups that NGS has encouraged to be formed by the American Society for Photogrammetry and Remote Sensing (ASPRS) and the American Association for Geodetic Surveying (AAGS). There are several Task Forces and Committees formed on the state level that are also working on adoption and implementation issues specific to their states.  Together, these efforts aim to build understanding, reduce uncertainty, and support the geospatial community’s successful implementation of the updated reference framework.   NSPS and NGS have committed to having a significant presence at Geo Week in Denver, Colorado, on February 16-18, 2026. 

    As mentioned in the working group’s report, “As an outgrowth of interaction between NSPS & NGS during NGS quarterly meetings and at geospatial events such as the ESRI User Conference and Geo Week, the NSPS leadership team and subsequently the NSRS Modernization Subcommittee began developing a suite of resources — including an ArcGIS StoryMap with several resources useful for the transition.   See the link for the NSPS ArcGIS Story map here: https://share.google/oOAIapPQnux5q8nwl.

    The box titled “NSPS ArcGIS Story Map” offers a detailed look at this resource, which visually illustrates the impact and benefits of the upcoming NSRS modernization.

    NSPS ArcGIS Story Map
    NSPS ArcGIS Story Map

    The website has five buttons:

    • Overview
    • What to Expect
    • How to Prepare
    • Resources
    • Note to Users

    The section titled “The Overview Section” details the essential information — who, what, where, when, and why — regarding the new, modernized NSRS.  Additional information is available on the website.

    Overview

    WHO: The  National Geodetic Survey  (NGS), located within the National Oceanic and Atmospheric Administration (NOAA) of the United States government.  The NGS is responsible for defining, maintaining, and providing access to the country’s positioning infrastructure called the  National Spatial Reference System  (NSRS).

    WHAT: Is updating the NSRS  – horizontal (geometric, NAD 83) and vertical (geopotential, NAVD 88 and local island vertical datums PRVD02, USVI09, ASVD02, GUVD04, HAWAII – Local Tidal) geodetic datums, an effort that has been underway since 2007.

    WHERE: The North American, Pacific, Caribbean, and Marianas plates.

    WHEN: Now – rollout is underway. An updated  Federal Register Notice was released on October 9, 2024.   Alpha and  Beta products are being released, with full replacement of the NSRS anticipated in 2026.

    WHY: These datums have been in use since GPS was in its infancy – i.e., for decades, and there are known limitations that the new system addresses:

    • NAD 83 is not as geocentrically defined as today’s positioning technologies demand, meaning not referenced to the center of Earth’s mass, by about 2.24 meters based on the latest international estimates. This is problematic when using Global Navigation Satellite Systems (GNSS), which orbit about and provide positions relative to the center of the Earth.
    • NAD 83 grouped the North American and Caribbean plates in its definition.  The updated system has broken those two plates out (because we now understand how to measure how the plates rotate individually) in addition to the Pacific and Marianas plates included in NAD 83, resulting in definitions for four Terrestrial Reference Frames (TRFs): NATRF2022, PATRF2022, MATRF2022, and CATRF2022.
    • Continental drift and vertical land movement were not accounted for in the existing NSRS.  Reference epochs (timestamps, for instance) for coordinates have been introduced for survey data to help us better understand movement or change over time.
    • Based on current international geoid estimates, NAVD 88 is biased by approximately 1.5 meters and tilted by 1 meter coast-to-coast.
    • There are currently multiple vertical datums.  The new system will consist of one.
    • NAD 83 and NAVD 88 were designed independently, resulting in reduced accuracy.  In the new system, they were designed together, resulting in better integration and higher accuracy.
    • GEOID 18 and previous models were hybrid models “warped” to match leveled benchmarks. GEOID2022 will be a more consistent and stable model as it is a purely gravimetric geoid model.
    • Currently, both physical marks and continuously operating GNSS stations are relied upon for the existing NSRS. Physical marks degrade and are destroyed over time, negatively affecting height and position data. The modernized NSRS will rely exclusively on GNSS stations.
    • State Plane Coordinate System 83 (SPCS 83) includes high levels of distortion for many areas. The modernized SPCS2022 minimizes distortion or scale error (the difference between ground and grid measurements) at the topographic surface rather than the reference ellipsoid surface, and is designed to minimize distortion in populated or high-use areas.
    • An important change between SPCS 83 and the upcoming SPCS2022 is that only the international foot (1 foot = 0.3048 meter, exactly) will be supported, which differs from SPCS 83, with some states officially using the international foot while others use the U.S. survey foot (1 foot = 1200/3937 meters). This is consistent with the  deprecation of the U.S. survey foot initiated by the National Institute of Standards and Technology (NIST) at the end of December 2022.

    The website makes it easy to spread the word about NSRS modernization. By clicking the share button on the right side of the page, you can access several ways to distribute the story map with colleagues or on social media.

    The Sharing the NSPS ArcGIS Story Map includes more details — it even includes an embedded QR code that you can scan to open the map directly on your mobile device.

    You can access it on your mobile device using the code below.

    NSPS ArcGIS Story Map QR Code
    NSPS ArcGIS Story Map QR Code

    For those who prefer a physical copy or a clean PDF, the site also offers a print-friendly version. See the box titled “NSPS ArcGIS Story Map – Print View” for instructions on how to access it. This 15-page document provides all the same information as the interactive site in a consolidated, easy-to-read format.

    NSPS ArcGIS Story Map – Print View
    NSPS ArcGIS Story Map – Print View

    As highlighted in the NSPS working group’s October report, both NSPS and NGS are committed to a major presence at Geo Week in Denver, Colorado, from February 16–18, 2026.

    A key session, “NSRS Modernization – The Latest Technical Updates,” is currently scheduled for February 17, 2026, at 2:00 PM. For more details on the presentation and speakers, refer to NSRS Modernization – The Latest Technical Updates below.

    2:00 PM – 3:30 PM MT

    Bluebird Ballroom 1A

    The National Spatial Reference System (NSRS) is undergoing a major transformation to provide more accurate, accessible, and consistent geospatial reference data across the United States. This session will present the latest technical updates on NSRS modernization, including advancements in geodetic reference frames, updated survey standards, and enhanced tools for positioning and measurement. Attendees will learn how these changes impact surveying, mapping, infrastructure, and engineering projects, and gain practical guidance for integrating modernized NSRS data into workflows. This session is essential for professionals seeking to stay current with the evolving national geospatial reference framework.https://mail.google.com/mail/u/0/#search/lfoster%40esri.com/FMfcgzQcqtcPbfppZtnTpZZWDMkQcXfk?projector=1&messagePartId=0.1

    I wish you all a prosperous 2026 filled with wonderful new relationships, exciting opportunities, and continued happiness and success.

    Happy New Year!

  • The rise of LEO PNT

    The rise of LEO PNT

    Today’s commercial innovation requires infrastructure that moves at the same pace.

    Essence

    The rise of commercial satnav

    Everyday life is saturated with location-dependent devices. They are multiplying faster than ever and their requirements have surpassed what GPS can support. Innovation in low-Earth orbit (LEO) satellites have seen exponential growth in the last ten years, unlocking new possibilities in further connecting our world.

    In 2016, the total number of satellites operational in space from commercial and government operators was approximately 1,500. This number had been stable for decades, with linear growth since the launch of Sputnik in 1957. Today, there are now more than 8,000 satellites operational in space — with nearly all growth happening in LEO.

    There are multiple reasons why. The cost of space access has decreased with reusable rockets and greater competition. The demand for connectivity has driven deployment of multiple constellations to deliver Internet from space. Latency is extremely important in communications and resolution in Earth observation.

    While innovation in LEO satellites has primarily focused on connectivity and Earth observation, there is a generational opportunity to innovate in the position, navigation and timing (PNT) infrastructure that silently powers modern life.

    There are now more than ten entities working toward deployment of dedicated PNT functions in LEO, amounting to more than 2,500 satellites if every constellation was complete today. As shown in Figure 1, five of these entities have already collectively launched more than 50 satellites. This market signal is not surprising, as demand for greater precision, power and protection are becoming fulfilled with diversification in LEO.

    Figure 1. Launches of LEO PNT satellites.
    Figure 1. Launches of LEO PNT satellites.

    Essentials

    Medium-Earth orbit (MEO) has been the traditional choice of satellite navigation for global systems, with GPS, Galileo, BeiDou and GLONASS all being deployed in this regime. This altitude in the outer Van Allen belts is the harshest radiation environment Earth orbit satellites are subjected to and is a major driver in the cost and complexity of the satellites. From a commercial standpoint, deployment in LEO is more attractive as the more benign radiation environment allows for the use of more commercial off-the-shelf (COTS) parts in satellite designs, facilitating volume production. With a healthy ecosystem and supply chain now developed around LEO for both satellites and launch vehicles, the opportunity for commercial PNT to set a new standard in performance and protection is open.

    The time for innovation in PNT could not be more urgent. Innovators are pushing the frontiers of technology across every industry and market. Physical intelligence is proliferating in the form of self-driving cars, humanoid robotics, automated farming, unmanned aerial systems and more. As these systems begin to coexist in the real world, the tools they rely on have never been more at risk. Commercial aviation is regularly jammed in Europe and the Middle East due to ongoing conflicts. And ships at sea are struggling to adapt to an environment where spoofing is commonplace.

    The commercial world has different and increasingly more stringent requirements than government-focused systems like GPS. GPS was designed primarily around military requirements and is longstanding infrastructure that is difficult to change with the myriad number of deployed devices that depend on it. This responsibility makes GPS too big to fail, but also incredibly difficult to change.

    GNSS infrastructure has unlocked so much in commercial activity. There are now more devices using GNSS than the Internet, and GPS is by far the majority user of the technology (based on nearly 7 billion active GNSS devices on Earth and around 6 billion users of the Internet.) However, commercial users have limited input to the evolution of GNSS constellations, which has led to a widening gap between technology and wants, which provides for the current commercial opportunity.

    Simply put, today’s commercial innovation requires commercial infrastructure that moves at the same pace to support.

    Elements

    Architecting LEO PNT

    For a LEO satellite navigation system, many designs could be considered, as reflected in Table 1 from Reid et al. (2025) outlining current public information about systems already announced. These constellations range from government-supported systems, which could act as extensions of already deployed global or regional systems, to commercial systems that target potentially unique, independent markets.

    Table 1. Comparison of dedicated LEO PNT systems, deployments, and plans. Note that satellites already deployed were verified on celestrack.org .
    Table 1. Comparison of dedicated LEO PNT systems, deployments, and plans. Note that satellites already deployed were verified on celestrack.org .

    These constellations all have one thing in common: they aim for between 200 and 300 LEO satellites. The reason is simple: as LEO satellites have a footprint of approximately 1/10th that of medium Earth orbit (MEO) satellites, and between 20 and 30 MEOs are required for global PNT, approximately 10x more LEOs are needed to obtain similar coverage. A consequence is that in LEO, the radio energy is spread over 1/10th the area compared to MEO, which has implications for power needs at the satellite — 10x less in LEO for the same MEO power in the same band.

    There is another crucial parameter to consider in LEO PNT design: spectrum. Table 1 shows that many approaches are being considered. Xona’s approach with its Pulsar constellation was centered around three major areas of commercial appeal: seamless operation with existing devices; increased native accuracy; and added resilience to jamming and spoofing. An important philosophy adopted early in the company’s culture was to not make development a science project — that is, do not reinvent the wheel, but rather upgrade the engine. GPS was a revolutionary technology, which is why it is so heavily adopted and brings so much value to the world. Therefore, stand on the shoulders of this giant to look out to the future.

    Ease of integration was the first consideration, as it has been the most important aspect in accelerating adoption of any new system. And spectrum is key to Integration. By launching a new system that uses the existing L-band signals, the GNSS ecosystem producing approximately one billion new units per year can seamlessly upgrade their capability without new hardware. Xona’s first technology pathfinder satellite in 2022 validated this hypothesis. While the pathfinder mission supported two satellite frequencies already in the regional navigation satellite system (RNSS) bands — one near L-band E6 and the other in the yet unused C-band near 5 GHz — it became apparent that receiver companies were willing to develop hardware for the L-band signal, and did so quickly with their existing hardware. There was resistance and longer timelines to global adoption for C-band signals.

    In response, Xona shifted the production signals to a dual L-band system, which already has nearly a dozen commercial receiver partners tracking the recently launched production satellite — some within weeks of the launch. The challenge is to choose a waveform that is near existing GNSS bands, familiar in form and function and digital signal processing techniques to what is already fielded today, and to not cause harmful interference to the existing GNSS services in orbit. The resulting design is shown in Figure 2, on the right. The key innovation was the selection of a bandwidth efficient form of quadrature phase shift keying (QPSK), which focuses the energy in the central lobe and rolls off quickly compared to a traditional binary phase shift keying (BPSK) signal, shown in Figure 2 on the left for comparison. The result is a 100x stronger signal that does not cause harmful interference to existing GNSS signals, while offering resilience through more signal power. This selection process was iterative, taking feedback from the receiver community. More information on the design and testing for compatibility can be found in Reid et al. (2025).

    Figure 2. (Left) GPS BPSK-based signal waveform, and (right) Pulsar QPSK-based signal waveform.
    Figure 2. (Left) GPS BPSK-based signal waveform, and (right) Pulsar QPSK-based signal waveform.

    In addition to compatibility and ease of integration, accuracy and resilience are critical design drivers. For example, farmers rely on their equipment positional accuracy to efficiently distribute seeds, fertilizer and water, reducing waste and improving crop yields. Positional accuracy also enables accurate, repeatable field operations year after year, saving time, fuel and money while protecting the soil. Because GNSS typically offers meter-level positioning, today many farmers buy positional accuracy through GNSS correction services to obtain centimeter-level positioning. The Xona architecture leverages these techniques in precise point positioning (PPP), delivering precise ephemerides direct from the space segment, and combining them with the fast motion from LEO satellites (compared to MEOs) to reduce position solution convergence times from ~10 minutes to nearly instantaneous (see, for example, Mah and O’Keefe, 2025). This geometry also boosts coverage, as correction services today typically rely on geostationary satellites and do not service high latitudes, where they would benefit missions such as mining operations for critical minerals and polar navigation.

    Connectivity relies on resilient timing. Passing more data through a network means efficiently meshing data packets in synchronized manner. Telecommunications and data centers need such connectivity to function. Authentication is expected in our communications systems, which is largely unavailable in civil GNSS signals. In an age where GNSS spoofing is done to cheat at games like Pokémon Go and now more frequently for nefarious purposes, authentication becomes essential for a modern system (Anderson, 2025, and Xona, 2025a). For resilience to spoofing, Xona included not just data authentication, but also range authentication, so that users can ultimately authenticate their position.

    Defense applications require resilience to jamming. World conflicts, particularly currently in Ukraine and the Middle East, have showcased GNSS vulnerabilities in the presence of widespread GNSS jammers. However, this problem is no longer only a defense issue. In 2025, nearly 123,000 commercial flights in Europe were disrupted between January and April alone by GNSS jamming (GPS World, 2025). For resilience to jamming, one method is more power. LEO being 20x closer to Earth than MEO affords nearly a 10x boost in power for the same power transmitted at the satellite. Xona’s target was 100x more power to the end user to significantly reduce the effective range of a jammer by more than six times as shown by recent field trials. Such a transmission power translates to a >97% reduction in affected area and means threats shift to larger and less practical platforms for adversaries, i.e., from requiring handheld devices to backpacks or even truck-sized jammers.

    More signal power also has implications for indoor positioning. Internet of things (IoT) devices such as asset trackers are commonly affected by signal obstruction and attenuation during transit, particularly in indoor environments, urban canyons, under foliage, or when obstructed by vehicles and cargo. Warehouses, shipping containers, and other constraints limit where position can be determined. Even coarse indoor positions can support operational intelligence for asset management.

    Launching LEO PNT

    Pulsar is designed to launch in stages as shown in Figure 3, which unlocks capability in tranches that expands the number of features and ultimately the user base. While Pulsar will achieve persistent coverage across major markets at the deployment of 16 operational satellites, earliest customers in time transfer will see value from Pulsar much sooner as an independent source of timing synchronization for devices with holdover clocks. At 16 satellites, Pulsar will achieve persistent 1-satellite-in-view service, unlocking precise time transfer and coarse positioning for stationary users, including indoors. Pulsar also provides a link to stream GNSS corrections, building on a partnership with Trimble. Full resilient positioning will come online with GPS-level satellite visibility. First in the midlatitudes, with 192 satellites, and then globally with the deployment of an additional 66 satellites into polar orbit, bringing the total to 258 operational satellites.

    Figure 3. Pulsar constellation satellite launch stages.
    Figure 3. Pulsar constellation satellite launch stages.

    Xona launched its in-orbit-validation stage in June 2025 with Pulsar-0, the first production-class satellite representative of the scaled capability in terms of signal modulation, power and features. Pulsar-0 allowed for performance validation of the complete system, not just of the payload in space but also the tangible benefit to users on the ground. For scale, Figure 4 shows the 150 kg class satellite pre-launch, including its integration on the Falcon 9 launch vehicle. Launch cost has been become more accessible, unlocking the ability to launch larger spacecraft by commercial entities, which can have larger positive impact on the ground (Xona, 2025b).

    Figure 4. Xona’s first production satellite Pulsar-0.
    Figure 4. Xona’s first production satellite Pulsar-0.

    LEO PNT on-orbit

    In almost 6 months since launch, Pulsar-0 has been tracked in more than 6 countries, 12 third-party receiver protypes, and has achieved several performance milestones that signal the groundbreaking capability Pulsar will deliver to users everywhere when the full constellation is operational. Early performance tests are built to showcase the value and features most important to commercial users in realistic settings.

    Accuracy. Figure 5 illustrates a signal-in-space user-range-error (SISRE) of 43 mm — about the diameter of a golf ball. This performance represents a more than tenfold increase in accuracy compared to that reported by GPS (Refro et al., 2024). The implication is an ability to natively perform PPP at the centimeter level, without an additional data link or correction layer.

    Figure 5. Estimate of SISRE for Pulsar-0 ranging signal compared with nominal GPS.
    Figure 5. Estimate of SISRE for Pulsar-0 ranging signal compared with nominal GPS.

    Security. Xona is the first organization to show pseudorange authentication from orbit, accomplished using the Pulsar-0 satellite within weeks of the launch (Anderson, 2025). Pulsar is built from the ground up to be secure by design, combining cryptographic authentication of both navigation data and satellite ranging signals with rapidly authenticated signal verification — aiming for a time-to-authentication of approximately four seconds. This layered security significantly raises the technical and financial bar for would-be spoofers. A spoofer spoofing a single satellite continuously should succeed in fooling one second of a Pulsar receiver’s ranging once every 130 years (Xona, 2025a).

    Jamming. Pulsar-0 signal testing has been conducted under live-sky jamming conditions at several jamming events, including Jammertest 2025 in Norway. These campaigns confirmed that using the Pulsar X5 signal can reduce the effective radius of a jammer by 6.3 times as compared to GPS L5 — in other words, less than 3% of the affected area compared to GPS. The same targeted power, bandwidth and type of jammer waveform was used against GPS and Pulsar, including center frequency. For context, Figure 6 shows the implications for a 1 Watt jammer scenario in San Francisco and the reduction brought by a 6.3x reduction in radius.

    Figure 6. ffective jamming areas for Pulsar X5 and GPS L5 from a 1 W jammer in San Francisco based on Jammerfest 2025 test results.
    Figure 6. ffective jamming areas for Pulsar X5 and GPS L5 from a 1 W jammer in San Francisco based on Jammerfest 2025 test results.

    Indoor. Data were collected for several navigation passes per day at multiple locations, including indoors. These include passes at Xona headquarters in Burlingame, California, and its office in Montreal, Canada. The most challenging indoor environment was Montreal, on the third floor of an industrial and primarily concrete building with two floors above. Figure 7 shows the Pulsar-0 power profile during a typical pass, peaking at the highest point in the sky. This structure is an artifact of the antenna gain pattern used in this mission. Designed for a higher altitude for deployment of later satellites, the pattern will be more isotropic with future satellites launched near 1100 km altitude compared to Pulsar-0, which is closer to 500 km. Near apex, the signal penetrates indoors, and this short segment proves to be sufficient for indoor positioning for stationary users. Leveraging techniques based on Doppler and including pseudorange, early results indicate sub-10 meters both outdoors and indoors. 

    Figure 7. Comparison of Pulsar and GPS signal strengths on roof and indoors at Xona Montreal office.
    Figure 7. Comparison of Pulsar and GPS signal strengths on roof and indoors at the Xona Montreal office.

    EVOLUTIONARY

    The coming years will be about gaining operational experience and in scaling the constellation with a near-term focus on the first batch of 16 satellites. Pulsar-0 has already confirmed its value proposition: attaining major milestones in performance including accuracy, security and jamming, but perhaps most importantly in the integration of user equipment. The next year is about working with customers in specific industries and use cases as Xona moves towards deployment of early operational service.

    The future of LEO PNT is bright. Theory has evolved to prediction, which is now evolving to reality. The early results appear to lead to an exciting PNT future with LEO PNT expanding the GNSS revolution in terms of security, interference mitigation and system availability both outdoors and indoors for a myriad of current and new applications and users.

    Further Reading

    Anderson J (2025). World’s First Authenticated Satellite Pseudorange from Orbit, Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025), Baltimore, Maryland, September 2025, pp. 738-748.

    Eissfeller B, Pany T, Dötterböck D and Förstner R (2024). A Comparative Study of LEO-PNT Systems and Concepts, Proceedings of the ION 2024 Pacific PNT Meeting, Honolulu, Hawaii, April 2024, pp. 758-782.

    FrontierSI (2024). State of Market Report on Low Earth Orbit Positioning Navigation and Timing (LEO PNT)

    GPS World (2025). 123,000 flights disrupted by GNSS jamming.

    Leclère J, Marathe T, Reid TGR (2025). Insights into Xona Pulsar LEO PNT: Constellation, Signals, and Receiver Design, Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025), Baltimore, Maryland, September 2025, pp. 3008-3096.

    Li W, Yang Q, Du X, Li M, Zhao Q, Yang L, Qin Y, Chang C, Wang Y, Qin G (2024). LEO augmented precise point positioning using real observations from two CENTISPACE™ experimental satellites. GPS Solutions, 28(1): 44.

    Mah C, O’Keefe K (2025). Hardware Simulation of Low-Earth-Orbit GNSS for Carrier Phase Ambiguity Resolution, Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025), Baltimore, Maryland, September 2025, pp. 2431-2443.

    Prol FS, Ferre RM, Saleem Z, Välisuo P, Pinell C, Lohan ES, Elsanhoury M, Elmusrati M, Islam S, Çelikbilek K, Selvan K, Yliaho J, Rutledge K, Ojala A, Ferranti L, Praks J, Bhuiyan MZH, Kaasalainen S and Kuusniemi H (2022). Position, Navigation, and Timing (PNT) Through Low Earth Orbit (LEO) Satellites: A Survey on Current Status, Challenges, and Opportunities, IEEE Access, (10): 83971-84002

    Reid TGR, Chan B, Goel A, Gunning K, Manning B, Martin J, Neish A, Perkins A and Tarantino (2020). Satellite Navigation for the Age of Autonomy, 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS), Portland, Oregon, April 2020, pp. 342-352.

    Reid TGR, Gala M, Favreau M, Kriezis A, O’Meara M, Pant A, Tarantino P and Youn C (2025). Xona Pulsar Compatibility with GNSS. Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025), Baltimore, Maryland, September 2025, pp. 929-943.

    Reid TG, Neish AM, Walter T and Enge PK (2018). Broadband LEO constellations for navigation. NAVIGATION: Journal of the Institute of Navigation, 65(2): 205-20.

    Renfro BA, Stein M, Reed EB, Finn A (2024). An Analysis of Global Positioning System Standard Positioning Service Performance for 2022

    Xona (2025a). The Next Era of Navigation Is Secure by Design. Blog by Jason Anderson.

    Xona (2025b). Road to Pulsar-0: From technology demonstrator to production-class satellite. Blog by Adrien Perkins. https://www.xonaspace.com/news/road-to-pulsar0

  • NASA preps Mars helicopter as war shapes defense tech future

    NASA preps Mars helicopter as war shapes defense tech future

    It’s always good news when we hear about NASA’s “out-of-this-world” next steps toward building a replacement for Ingenuity, the small Mars helicopter-drone. With 72 flights over 1,004 days, Ingenuity outlived NASA’s expectation of just 30 operational days on Mars. It ended up serving as a trailblazer for the SUV-sized Perseverance rover as it worked its way around Jezero Crater. Built with a large number of smartphone components, it’s actually amazing that this thing survived for so long, given the radiation environment on the surface of Mars, along with the harsh temperature extremes of daytime 32°F to nighttime minus 130°F. How a Samsung S5 phone battery survived, operating so far outside its design temperature range, is hard to fathom.

    NASA’s 20-year plan for future Mars exploration now looks to take advantage of the huge expansion of the envelope for exploration that the small 30-day Mars helicopter brought to the Perseverance mission: “Enhanced mobility systems will enable exploration of challenging terrains and increased operational range. Aerial mobility technologies will facilitate access to previously unreachable areas on Mars.”

    NASA drone flies over ‘Mars Hill’ in Death Valley during recent navigation tests (Photo: NASA/JPL)
    NASA drone flies over Mars Hill in Death Valley during recent navigation tests. (Photo: NASA/JPL)

    So now NASA is working on the next Mars rover mission and on improvements for its accompanying airborne support. A team recently took three commercial drones into Death Valley to work on overcoming navigation problems that Ingenuity encountered on Mars flying over “bland” terrain with few visual features for its optical navigation system. Sand dunes without features on Mars messed with Ingenuity’s navigation solution, including on its 72nd flight.

    Death Valley and Mesquite Flats Sand Dunes were two places the NASA team visited to test improved navigation algorithms installed on existing commercial drones, and they found some improvements by adding camera filters. The new software helped find landing spots in cluttered terrain.

    But now new initiatives are seeking ways to get crewed flights to Mars in the next couple of years, well ahead of NASA’s timetable, which doesn’t move to anything crewed until around 2030. NASA still seems to prefer to pursue landers to gather much more data on Mars before risking crewed flights. Robotic dogs are also being investigated that can traverse rugged uphill areas that landers cannot access, as well as a winged glider the size of a small school bus.

    Meanwhile, the never-ending Russia-Ukraine war rages on, dominated by drone attacks from both sides. Russia is increasingly using Iranian Shahed or the equivalent Russian-produced Geran-2 one-way drones, while Ukraine intercepts them with low-end modified commercial drones. This stalemate has $20,000 Geran-2 drones being brought down by high-speed interceptor drones built for $2,000 to $6,000 — in other words, the cost of attrition might determine the victor.

    Russian Geran-3 jet-powered drone downed by Ukraine. (Photo: DIU)
    Russian Geran-3 jet-powered drone downed by Ukraine. (Photo: DIU)

    However, Russia has now introduced a jet-powered Geran-3 model that flies at up to 230 mph, which Ukraine has apparently been able to bring down.

    As we well know, Ukraine not only regularly receives Western military equipment but also civilian drones in large numbers. But an industrial capability has also been created in Ukraine to design, develop and build high volumes of drones. So it’s not surprising that Ukraine has revealed its own interceptor drone known as Sting.

    STING interceptor drone and imagery striking a Shahed drone. (Photo: Wild Hornets Group)
    STING interceptor drone and imagery striking a Shahed drone. (Photo: Wild Hornets Group)

    Nevertheless, Sting has four rotor props and should be no match for a Geran-3 flying at top speed, even though Sting is claimed to be capable of 215 mph. The Russian jet-powered drone also apparently comes with anti-jam capabilities and a satellite navigation system, but Russia has yet to field these new drones in large numbers. Of course, Ukraine says it has already developed jet-powered interceptor drones — so the step up to the next level of technology should happen for both sides, but of course, costs increase for both sides, which neither can really afford.

    Defense has always affected the speed of development for any technology — government funding and oversight are major incentives for new companies to emerge and for new technologies to be developed. Anduril Industries has recently emerged as a new entrant to the U.S. industrial defense complex, specializing in autonomous systems. Anduril’s products include unmanned aircraft systems and counter-UAS, and they have made big strides in both areas.

    Anduril is a relatively new company, initially founded in 2017, so its products are fresh off the drawing board and its product improvement experience is at best eight years. The big U.S. defense contractors have fielded and corrected decades of problems in their high-tech systems, so new generations come with hard-learned design and build understanding. The advantage for Anduril is that they are not bound by the restrictions of a long-established industrial heritage, but this can also mean they may still have a way to go in learned experience.

    Nevertheless, in high technology, much is new technology and new software and new approaches to build. So it takes effort to not only make this stuff work but also to make it work reliably.

    Altius — 33lb warhead attack drone. (Photo: Anduril)
    Altius — 33lb warhead attack drone. (Photo: Anduril)

    Anduril builds lots of test articles and rapidly evolves the design through rigorous internal and real-world testing. So it’s not uncommon to see test failures — this is how improvements are developed.

    Recent U.S. defense tests that saw crashes at Eglin Air Force Base in Florida drew a lot of bad press, given that the Altius drone had already been battle-tested in Ukraine. However, if the approach of lower cost, high volume and attritable drones is the one we have chosen, it may take a little more time to get maturity into the beast.

    Navigation testing for NASA’s next Mars drone, jet-powered attack drones, and evolving interceptor defenses and drones from a new player on the U.S. defense scene — a pretty wide range of unmanned aircraft applications.

  • Opinion: The truth about NextNav’s 5G-powered 3D PNT

    Opinion: The truth about NextNav’s 5G-powered 3D PNT

    On Nov. 11, the chair of the Z-Wave Alliance, Avi Rosenthal, published an opinion piece in GPS World, urging a delay in addressing one of America’s most pressing national security and economic vulnerabilities. I am talking about the need for a terrestrial complement to GPS. By ignoring both the urgency of the threat and the strength of the engineering analysis supporting near-term solutions like 5G-powered 3D PNT, Mr. Rosenthal argues the U.S. can afford to wait. At NextNav, we strongly disagree.

    Around the world, GPS disruptions are no longer hypothetical. As this publication has documented, incidents of GPS jamming and spoofing have become routine in places like the Middle East and the Baltic states. And the increasing severity of these disruptions is spilling over into civilian life, putting us all at risk. We’ve seen the consequences here at home, too. Major airports have experienced manmade GPS disruptions of unknown origin, and farmers have seen how even temporary GPS loss can upend precision agriculture.

    Whether caused by jamming, spoofing or natural disasters, the vulnerabilities are real and growing.

    These threats are why the Federal Communications Commission (FCC) made it a priority to advance additional technologies and solutions as part of a whole-of-government approach to strengthen PNT resiliency. At NextNav, we are doing the hard work necessary to help enable a system-of-systems capable of delivering greater PNT resilience into America’s critical infrastructure, while Mr. Rosenthal and his allies continue to rely on flawed studies and broad mischaracterizations of our proposal. They preach delay rather than moving to the logical next step of the FCC process, specifically designed to allow the commission to fully evaluate competing technical claims.

    We have filed multiple comprehensive engineering studies demonstrating that 5G operations in the lower 900 MHz band will not cause unacceptable interference to unlicensed devices. Those studies specifically examined five different unlicensed technologies, including the Z-Wave technology. To ensure this discussion is fact-based, we’d like to set the record straight.

    The SIA-sponsored paper that Mr. Rosenthal cited for his unrealistic claims of interference does not hold up under scrutiny and contains a number of fundamental technical errors. As we’ve outlined in detail, NextNav’s detailed technical analysis has identified significant flaws in the Pericle paper, pointing out fundamental errors in the paper’s assumptions and methodology.

    For instance, Pericle’s predicted 5G emission levels exceed levels found in theoretical free-space conditions — an impossibility that undermines the entire paper. The Pericle paper also seems to ignore how 5G positioning signals work, failing to mention comb patterns and muting that are core to the technology, and thereby further inflating perceived 5G emission levels. Attempts to reproduce Pericle’s simulations with Pericle’s stated methods and parameters yield dramatically different results, which serve as clear evidence of computational errors or faulty execution of the depicted scenario.

    Perhaps most remarkably, no credible analysis could replicate Pericle’s conclusion that 5G interference would occur more than 50 percent of the time when the ostensibly interfering transmitter operates only 50 percent of the time.

    The most glaring issue with the paper that Rosenthal cites is that it never directly analyzes the very devices that the security industry states are predominant in home and business security systems today. Specifically, it fails to analyze Z-Wave, the technology that, according to the Z-Wave Alliance, is utilized by more than 90% of professionally monitored security systems in North America. In fact, Z-Wave operates primarily on frequencies that are outside of the frequencies which NextNav’s proposes to use for 5G.

    It is a fact that unlicensed lower 900 MHz devices today successfully coexist with a wide range of unlicensed users that operate without coordination or interference protection. Pericle never accounts for the resilience mechanisms Part 15 devices use every day, including frequency hopping, bursty transmissions, adaptive modulation, redundant paths (meshing), self-healing and other features.

    Lastly, Mr. Rosenthal’s characterization of the Department of Transportation’s action also fails to mention that the DOT has already evaluated NextNav’s technology, ranking NextNav first in every category of its 2021 evaluation. In 2024, DOT awarded NextNav the largest grant, $1.8M, for Rapid Phase I field testing of PNT technologies. NextNav supports DOT’s ongoing work to advance complements to GPS, but its testing should not stand in the way of swiftly advancing solutions that are ripe for action now.

    Waiting for DOT to conclude its testing of multiple additional PNT technologies before the commission acts within its authority to take the next step towards enabling one or more potential solutions not only runs contrary to a Presidential Executive Order for agencies to remove barriers to private sector investment, but also risks the same analysis paralysis that slowed deployment of resilient PNT in the previous administration.

    At NextNav, we are serious about solving an urgent national security problem, and we will continue to do the hard work necessary to support the FCC’s engineering-driven decision making. The FCC is the expert authority on commercial spectrum issues, and we believe it has all of the information it needs to take the next step in this process by issuing a Notice of Proposed Rulemaking (NPRM). Issuing an NPRM would also give the FCC the opportunity to ask any remaining technical or economic questions that it may deem necessary to complete its evaluation.

    It’s time to roll up our sleeves and do the hard work necessary to enable a system-of-systems approach to building great PNT resilience. The longer we delay, the more vulnerable we become.

    Renee Gregory is the vice president of regulatory affairs at NextNav.

  • AAGS YouTube seminars on geodetic topics in support of a certificate in geodetic surveying

    AAGS YouTube seminars on geodetic topics in support of a certificate in geodetic surveying

    My May 2025 GPS World newsletter highlighted the American Association for Geodetic Surveying (AAGS) “Certificate for Geodetic Surveying” Program. This newsletter will update readers on the program. As I mentioned in the May 2025 newsletter, the Certificate for Geodetic Surveying program is designed to meet the needs of surveyors and others who perform spatial analyses and computations using geodetic methods. 

    Some of you may not be familiar with AAGS. The American Association for Geodetic Surveying (AAGS) aims to guide the community of geodetic, surveying and land information data users into the 21st century by working together to develop new educational programs — such as presentations, seminars, and workshops on geodetic surveying — and by publishing articles and papers that share the latest scientific and technological advances, along with advice for cost-effective, efficient implementation. AAGS also encourages a deeper understanding of geodesy by offering educational materials in geodesy, geodetic surveying and related fields.


    The AAGS Board meets on the second Wednesday of each month at 4:00 p.m. (Eastern Time). Please visit the AAGS website and consider joining our monthly board meetings — a forum to share ideas and learn about geospatial products and services. All are welcome. To be added to the attendee list, email me at [email protected].

    Here’s the latest on the certification program: AAGS has developed questions covering the seven core areas of minimum competence in geodetic certification: (1) Geometric Geodesy, (2) Physical Geodesy, (3) Accuracy and Error, (4) Temporal Aspects, (5) Global Navigation Satellite Systems, (6) Geodetic Survey Networks, and (7) Standards and Guidelines. For details on each topic, see my May 2025 GPS World newsletter. The information below includes examples the Board is considering for the exam.

    AAGS Geodetic Certification Exam — Sample Questions

    In the ECEF coordinate system, the X and Y axes define

    1. minor axis of a reference ellipsoid
    2. spin axis of the Earth
    3. prime meridian and north pole
    4. |equatorial plane
    • Physical Geodesy

    The term ‘deflection of the vertical’ applies to what?

    1. Error introduced when the curvature of the earth is not accounted for
    2. The angular difference between the perpendicular to a reference ellipsoid and perpendicular to the field of gravity at a location.
    3. The distortion induced on the Earth’s gravitational field by a large mass beneath the surface
    4. The difference between true and geodetic North at a location.
    • Accuracy and Error

    A __________________ is the difference between the observed value and the most probable value.

    1. blunder
    2. residual
    3. standard deviation
    4. systematic error
    • Temporal Aspects

    What is the purpose of National Geodetic Survey’s EPP model?

    1. To transform ITRF coordinates to NAD 83 (2011) Epoch 2010.00.
    2. To transform ITRF coordinates to a 2022 Terrestrial Reference Frames Epoch 2020.0 (a way of describing a plate’s rotation).
    3. To transform ITRF coordinates to WGS84 Epoch 2020.00.
    • Global Navigation Satellite Systems (GNSS)

    The satellite ______________________ sets up an arbitrary threshold below which GPS satellites should not be measured.

    1. azimuth
    2. inclination angle
    3. mask angle
    4. zenith angle
    • Geodetic Survey Networks

    In a GPS network adjustment, primary reason for the minimally constrained adjustment is to ensure that

    a) the baseline components are free of large errors

    b) the control point coordinates have no errors

    c) the degree of freedom of adjustment is correct

    d) integer ambiguities have been determined correctly

    • Standards and Guidelines

    Which of the following statements about the State Plane Coordinates System (SPCS) is false?

    1. Eliminates having individual adjacent surveys based on different assumed coordinates
    2. Extensive highway projects can start at one control point and close on another at some distance away.
    3. If a monument is lost, one can use other SPCS monuments to recover the lost monument.
    4. Since SPCS utilizes a “developable surface” to project ground points onto a plane, the resulting projection is “distortion free”

    The draft questions are under expert review to ensure they target the right geodetic concepts and effectively assess the knowledge needed by those creating geospatial products and services. Our aim isn’t to make everyone a geodesist, but to ensure anyone producing geospatial products understands enough geodesy to create, depict, and document them correctly. AAGS is partnering with NSPS to implement the program, aiming for a 2026 launch. I’ll share updates in future emails.

    Many are asking whether AAGS will create training materials to support the certification program. We do not have any official plans at this time. However, Muge Albayrak—an AAGS Director and researcher at Oregon State University—has been working with members to produce YouTube sessions on certification-related topics. So far, AAGS has released four sessions: (1) Astronomical Techniques in Geodesy, (2) Practical Precise Point Positioning (PPP): Properties and Performance, (3) Real-Time GNSS Networks – RTN Alignment – User Perspective, and (4) Real-Time GNSS Networks – RTN Alignment – Managing RTNs.

    We’ve discussed producing shorter YouTube sessions focused on key concepts from the seven competency areas of the geodetic certification program. These would complement the existing member-only educational videos on the AAGS website. For details, see the Resources tab on the AAGS website.

    YouTube of Real-Time GNSS Networks: RTN Alignment — User Perspective and Managing RTNs.

    The American Association for Geodetic Surveying The American Association for Geodetic Surveying

    New 4-Part Educational Video Series on Real-Time GNSS Networks (RTNs) – RTN Alignment
    The American Association for Geodetic Surveying (AAGS) is pleased to share a comprehensive four-part video series focused on Real-Time GNSS Networks (RTNs) and RTN Alignment — a topic that continues to grow in importance as more agencies, universities, and private organizations operate or rely on RTNs.
    This series brings together academic researchers and industry practitioners to provide clear user-level guidance and practical network-management insights grounded in current research and real-world field experience.
    Part 1 — RTN Alignment-User Perspective: Lecture : https://lnkd.in/eMuBqRkz
    Chase Simpson (Assistant Professor of Practice, Oregon State University) explains RTN fundamentals, field procedures, accuracy expectations, and how to combine real-time GNSS with conventional surveying.
    Part 2 — RTN Alignment-User Perspective: Q&A: https://lnkd.in/e_5vcM7Y
    A panel discussion addressing weighting strategies, redundant observations, GEOID2022 implications, and best practices for verifying RTN accuracy in the field.
    Part 3 — Managing RTNs: Lecture: https://lnkd.in/eV5P-daq
    William Ohene (PhD Student, Oregon State University) presents new research on monitoring core station stability, detecting reference station issues, and aligning RTNs with the National Spatial Reference System (NSRS).
    Part 4 — Managing RTNs: Q&A: https://lnkd.in/ejpkJq2Z
    A follow-up discussion on operational considerations for RTN managers, network density, coordinate updates, and improving user confidence across real-time networks.

    Why AAGS is sharing this series
    As part of our mission to support professional education and strengthen the geodetic surveying community, AAGS is committed to providing accessible, high-quality resources on emerging practices, technologies, and research.

    This RTN series supports surveyors, geodesists, GIS professionals, and RTN operators who rely on accurate real-time positioning.

    Watch the full 4-part series here: https://lnkd.in/ejvF6qQQ

    AAGS extends our appreciation to:
    • Lecturer: Chase Simpson
    • Lecturer: William Ohene
    • Moderator: Dave Zilkoski
    • Panel contributors: Karen Meckel, Müge Albayrak, and Brian Weave

    We hope this series supports your professional practice, education initiatives, and technical development.

    Please feel free to share your thoughts or questions — we welcome community discussion.

    As noted, AAGS members can access educational material on the AAGS website covering geodetic topics that will help answer many exam questions. Numerous external resources are also available. For example, NOAA’s National Geodetic Survey (NGS) offers webinars, online lessons, and educational videos, and GeoLearn provides continuing education courses for surveyors.


    Please visit the AAGS website and consider attending our monthly Board meetings. If you’d like to attend, want more information about AAGS, are interested in serving on a committee, or wish to collaborate on YouTube sessions about geospatial topics, email me at [email protected].

  • GPS Editorial Advisory Board: Expert takes on GNSS protection

    GPS Editorial Advisory Board: Expert takes on GNSS protection

    Among the technical approaches being researched this year for GNSS/PNT protection, which do you consider most effective or promising?

    Photo: Jules McNeff
    Photo: Jules McNeff

    “The simple answer is what I have been saying many times before. The most effective way to back up GPS/GNSS is to use the terrestrial technology available from eLoran.  It is affordable, long-range, precise and essentially unjammable. However, it’s not what I would call ‘promising’ because that’s not what the government wants to hear. In fact, the government is in the process of dismantling the existing Loran infrastructure that could easily be recapitalized as autonomous eLoran stations. eLoran could provide robust nationwide timing and positioning preservation, including in the northern Pacific Ocean and Alaska, as well as across the Arctic, with Canada, to link up with our allies in the UK and Europe, who are also investing in eLoran. There is no real commercial market in the far north and there are no commercial systems proposed that can provide such coverage in those areas where we are facing challenges from Russia and China today and that will only increase into the future.”

    — Jules McNeff

    Allison Brown
    Allison Brown

    “L-band jamming and spoofing is now prevalent in many parts of the world. It has now been confirmed that space-based jammers have been active, as well as conventional terrestrial jamming.  Anti-jam solutions can only provide protection up to a certain jammer power level and are not a ‘silver bullet’ solution. Moreover, nulling of space-based jammers will also have the effect of nulling parts of the sky where GPS satellites are in view, degrading performance by reducing DOP. Alternative PNT solutions that are not relying on L-band signals are the most effective solution for operations in highly contested, jammed or spoofed L-band environments.”

    — Allison Brown

    Photo: Mitch Narins headshot
    Mitch Narins

    “I believe that both orbital and ground-based PNT systems, operating in tandem and integrated properly, are the ultimate solution for critical infrastructure applications, but to get there, ‘the budget-office-inspired problem’ of having to pick one and only one must be abandoned: prevention is usually cheaper than curation. Only after space-based and ground-based PNT designers, developers, regulators and users understand and welcome the essential nature of PNT source diversity will we actually achieve the resilient PNT capabilities that we all need.”

    — Mitch Narins

  • UAV updates: DARPA advances UAVs, Area-51 RQ-170 investigation expands and more

    UAV updates: DARPA advances UAVs, Area-51 RQ-170 investigation expands and more

    Most people appear to be silently waiting for artificial intelligence (AI) to come up with a meaningful application beyond replicating jobs — one that actually helps people accomplish new tasks.

    Daily news reports show one of the so-called “Magnificent Seven” technology companies pouring another billion dollars or more into AI data centers or basic development. Well now, the Defense Advanced Research Projects Agency (DARPA) has found a smaller AI company to develop a novel application for UAVs.

    VISTA X-62A autonomous aircraft (Photo: Alex Lloyd/USAir Force)
    VISTA X-62A autonomous aircraft (Photo: Alex Lloyd/U.S. Air Force)

    PhysicsAI has contributed AI “agents” to a highly modified F-16 for machine perception, intelligent behavior, control and adaptive learning to create an autonomous UAV, according to available information. The VISTA X-62A participated in a manned-unmanned dogfighting demonstration in September 2023, though the outcome has not been disclosed. Other platform enhancements include intelligent sensors through computer vision, EO/IR/RADAR sensor fusion and virtual reality simulations.

    DARPA has engaged PhysicsAI to enhance UAVs so they can extend range and mission length by “soaring” — the technique birds use to find thermals in the atmosphere to climb to higher altitudes. AI agents will be designed, trained and tested to evaluate dynamic wind conditions, optimize flight profiles and perform soaring maneuvers.

    DARPA intends to develop AI agents that will extend endurance by employing this bird-like soaring capability to reduce UAV onboard power usage and extend range and mission duration.

    There is nothing new to report on the apparent drone crash Sept. 25, 2025, near the secretive base in Nevada, known as Area 51. The aircraft was attached to the 432nd Wing/432nd Air Expeditionary Wing at Creech Air Force Base in Nevada, about 57 miles southwest of the crash site. The 432nd operates MQ-9 Reaper drones, but the 33rd and 44th Reconnaissance Squadrons are also known to operate out of Creech and may operate RQ-170 Sentinel stealth drones.

    RQ-170 Sentinel Stealth Drone thought to operate out of Cheech AFB Nevada (Photo: Lockheed Martin)
    RQ-170 Sentinel stealth drone thought to operate out of Cheech AFB Nevada (Photo: Lockheed Martin)

    Famous (or infamous) for a 2023 reconnaissance operations in Iran, where one aircraft was apparently captured by the Iranians, the RQ-170 has been around since 2021.

    The mystery surrounding the crash near Area-51 has grown somewhat since an inert training bomb and an aircraft panel were discovered at the crash site, but these items were not part of the damaged/destroyed crashed aircraft. In addition, the Air Force Office of Special Investigations (OSI) and the FBI have now been brought in to investigate. Enthusiasts who managed to get to the crash site recently found it cleaned completely, with no sign of spilt fuel or debris.

    Troops in the field need information most — where the enemy is, their capabilities and what they’re doing.

    One option: Launch a drone with video, infrared and radar, then use whichever works best depending on lighting, weather and whether the enemy jams signals. Better yet, call in a high-altitude surveillance drone like a GA-ASI Reaper that the enemy can’t see or hear. But that takes time, and one might not be available.

    A new concept builds on an old precept — climb a tree and look at the opposition. But trees can be hard to find, difficult to climb and not high enough.

    The answer to jamming and observational altitude: a tethered drone that a squad can carry. If the squad has a truck or Humvee, it can launch a tethered drone with no time limits because power comes up the tether with driving instructions while visual data goes back down. If necessary, move the ground vehicle closer and the drone moves with it.

    Tethered drones serve any operation needing overview — rescue teams in disasters needing to see farther or a temporary communications hub, security operations searching for someone or something, monitoring or observing for infiltrators, initial surveys of difficult-to-access locations or military operations. Many other applications exist.

    Most commercial and first-responder operations favor commercial or heavy-lift multirotor drones. Companies using multirotor drones include Hoverfly, Zenith, Fotokite, USaS, Advexure, Elistair, Kratos and Volarious.

    Elistair Khronos Tethered DroneBox. (Photo: Elistair)
    Elistair Khronos Tethered DroneBox. (Photo: Elistair)
    Kratos Aethon Tethered Drone. (Photo: Kratos)
    Kratos Aethon Tethered Drone. (Photo: Kratos)

    If tethering drones to get really high, maybe use an aerostat that TCOM claims can operate from ground level to the stratosphere — pretty long tether needed! But applications also include anti-drone systems used to track and disrupt drone intruders.

    Then a more recent entrant is Windlift who uses a fixed wing multi-prop drone on the end of a very long tether to gain altitude and to operate in the sort of wind conditions that might be found at times in many locations world-wide, on land or at sea — very windy to gale force winds, actually up to 55mph. Now this is pretty tough for any tether system, but Windlift has a variable cross section tether which mitigates wind-resistance. And their special application is to fly in a figure of eight pattern at high altitude — to generate electricity.

    Windlift surveillance drone(Photo: Windlift)
    Windlift surveillance drone (Photo: Windlift)
    Windlift power generator (Photo: Windlift)
    Windlift power generator (Photo: Windlift)

    This month brings a mixed bag of drone news, ranging from AI-driven “soaring” drones to an Area 51 drone crash mystery and an overview of tethered drones and their applications, including power generation. Who could have forecast these drone applications? Well, maybe the crashing part.