Author: Tracy Cozzens

NGS releases annual experimental geoid models and gravity interpolation tools

My last column highlighted an ArcGIS web application that incorporates various datasets and data layers to assist surveyors planning vertical control surveys. On Jan, 29, the National Geodetic Survey (NGS) released the latest experimental geoid model, xGeoid20, and a new gravity interpolation tool (see box below, “NGS Releases Annual e& Gravity Interpolation Tools”).

This newsletter will highlight some attributes of these two new products. First, why am I writing about another experimental geoid model. I discussed xGeoid18 in my December 2018 column and xGeoid16 in my June 2017 column. What’s important here is that this will be the last experimental geoid model until 2022, and the dynamic geoid model has also been updated this year in the form of xDGEOID20.

xDGEOID20 is produced by NGS within the Geoid Monitoring Sƒervice (GeMS) and is part of the new NAPGD2022. Therefore, users only have a few more years to understand the differences between the hybrid geoid model that is being used today to estimate GNSS-derived orthometric heights and the gravimetric geoid model which will be used to estimate North American-Pacific Geopotential Datum of 2022 (NAPGD2022) GNSS-derived orthometric heights.

NGS also announced a new gravity tool, denoted as “The Experimental Gravity Model 2020 (xGRAV20).” xGRAV20 is designed to provide a full-field gravity value and a digital elevation model height at a-specified location. The xGRAV20 model will be important to users that are computing leveling-derived orthometric heights consistent with NAPGD2022.

It is important to note that the xGEOIDs provide a preliminary but increasingly-accurate view of the changes expected from the upcoming NAPGD2022. Also, the xGEOID20 geoid model is the first combination of the geoid models computed by scientists at NGS and Canadian Geodetic Survey (CGS). One unique element to xGEOID20 is that the differences between the A and the B model are due to the contribution of the GRAV-D airborne gravity and differences in methodology.

The National Geodetic Survey (NGS) has published annual experimental geoid (xGEOID) models since 2014. Each of these experimental geoids demonstrate the improvements provided by the addition of airborne gravity data (GRAV-D data) and by the refinement of geoid computation methods.

NGS Releases Annual Experimental Geoid Models & Gravity Interpolation Tools. (Image: NGS) — **NGS Releases Annual Experimental Geoid Models & Gravity Interpolation Tools.** (Image: NGS)

First, users can access the xGeoid20 model here. See the box titled Experimental Geoid Models 2020 (xGEOID20).

Experimental Geoid Models 2020 (xGEOID20). (Image: NGS) — **Experimental Geoid Models 2020 (xGEOID20)**. (Image: NGS)

As the image above indicates, the xGEOID20 is available over a very large area. The box below lists the latitude and longitude boundaries of the areas where xGeoid20 is available.

Areas Where xGeoid20 Model Is Available. (Image: NGS) — **Areas Where xGeoid20 Model Is Available.** (Image: NGS)

To use the xGeoid20 Interactive Computation Page, the user can click on the “ACCESS TOOL” button below the map or the Interactive Computation button on the left side of the webpage (see the image above, “Experimental Geoid Models 2020 (xGEOID20)”). I’d like to highlight a statement that NGS added as a note on the computation page:

Coordinates will be processed as IGS14.
The epoch should be in decimal year format and reflect the user-specified output epoch. If no epoch is entered, the tool will use a default epoch equal to the epoch of the static geoid model, which is currently 2020.00.

The user needs to know that the epoch is used to compute the xDGEOID20 value. I will demonstrate how this works later in this column.

xGEOID20 Interactive Computation Page. (Image: NGS) — **xGEOID20 Interactive Computation Page.** (Image: NGS)

As in past xGeoid interactive computations web applications, the user can submit data in various formats. The box titled “Input Formats Permitted for xGeoid20 Webtool” provides a list of the permitted formats. It should be noted that inputting an ellipsoidal height, epoch and name are optional. However, the default epoch is 2020.00, so if you want a different epoch, you need to enter the date. Also. the program will only compute an orthometric height if the user provides an ellipsoidal height.

Input Formats Permitted for xGeoid20 Webtool. (Image: NGS) — **Input Formats Permitted for xGeoid20 Webtool.** (Image: NGS)

Users have the option of getting the output from the xGeoid20 tool on their computer screen or in the CSV format. The box below is an example of inputting data using the screen option. Once you enter your data, the user clicks on the submit button.

Example of Input Format for Screen Option. (Image: NGS) — **Example of Input Format for Screen Option.** (Image: NGS)

The next image shows an example of the output using the screen option. I have highlighted a few numbers that I’d like to address.

Your input in NAD83 (2011) epoch 2010.00 (red). I entered my coordinates as NAD 83 (2011), and it assumed that these coordinates are epoch 2010.0.
Your Result in IGS14 epoch 2020.00 (blue). The routine provides your output coordinates in IGS14, epoch 2020.00. This is the epoch of the static geoid model.
The geoid height of GEOID18 (with respect to NAD83) and the orthometric height in NAVD88 (based on GEOID18) (green). This NAVD 88 value is for comparison purposes only. It is using GEOID18 and provides an estimate of the differences between the future NAPGD2022 and the current NAVD 88. The orthometric height is computed using the following formula: NAD 83 (2011) ellipsoid height (epoch 2010.0} minus GEOID18.
Ortho Height (brown). This is the estimation of the orthometric height using the following formula: IGS14 ellipsoid height (epoch 2020.0} minus xGEOID20A (or B).
Ortho(model)-NAVD88(GEOID18) (purple). These differences are the estimates of the differences between the future NAPGD2022 and the current NAVD 88. It provides the differences for both the xGeoid20A and xGeoid20B model. I look at the B model because it used the GRAV-D data in the development of the model.
Accuracy (yellow). This is the estimated 95% confidence interval for geoid height.

Example of Output Format from Screen Option

xGEOID20 Interactive Computation Output

Note: The GRS80 ellipsoid is used for both NAD83 and IGS14.

N: The geoid height at epoch t0 = 2020.0, which is geocentric and relative to the GRS80 reference ellipsoid.

Accuracy: Estimated 95% confidence interval for geoid height.

DN: The time-dependent geoid change computed between user inputted epoch (t) and t0. To obtain the dynamic geoid height at user inputted epoch (t), add N + DN.
Either Model A or Model B N values may be used for this depending on user preference.

Example of Output Format from Screen Option. (Image: NGS) — **Example of Output Format from Screen Option.** (Image: NGS)

The box below shows an example of inputting data using the CSV option.

Example of Output Format from CSV Option

Note: The GRS80 ellipsoid is used for both NAD83 and IGS14.

N: the geoid height at epoch t0 = 2020.0, which is geocentric and relative to the GRS80 reference ellipsoid.

Accuracy: Estimated 95% confidence interval for geoid height.

DN: the time-dependent geoid change computed between user inputted epoch (t) and t0. To obtain the dynamic geoid height at user inputted epoch (t), add N + DN. Either Model A or Model B N values may be used for this depending on user preference.

Cnt,Station,NAD83_Lat,NAD83_Lon,NAD83_Eht,Input_Epoch,
IGS14_Lat,IGS14_Lon,IGS14_Eht,Output_Epoch,GEOID18_
Ht,Oht_NAVD88,xGEOID20A_Ht,xGEOID20B_Ht,xGEOID20A_Accuracy,
Oht_xGEOID20B,Oht_NAVD88,Oht_Diff(xGEOID20A-NAVD88),Oht_Diff(xGEOID20B-NAVD88),DN,Epoch

0,PA,40.616935533762,77.4066810996784,222.425581993569,
2010.00,40.6169445389,77.4066880139,221.191,2020.00,
-33.685,256.111,-34.475,-34.477,0.039,255.666,255.668,
-0.445,-0.443,0.000,2020.0001,PR,18.2570177272727,66.5508117355371,
6.65385123966942,2010.00,18.2570227778,66.5508102806,
4.776,2020.00,-39.379,46.033,-41.690,-41.679,0.040,46.466,46.455,
0.433,0.422,0.000,2020.000

Example of Input Format for CSV Option. (Image: NGS) — **Example of Input Format for CSV Option.** (Image: NGS)

The printed output from the CSV option looks very confusing, but it can be imported into an excel spreadsheet. The headings and values are all separated by a comma so everything falls into the appropriate columns after importing the data (see image below.)

Example of CSV Output Format Imported into Excel. (Screenshot: David Zilkosky) — **Example of CSV Output Format Imported into Excel.** (Screenshot: David Zilkoski)

Example of CSV Output Format Imported into Excel. (Screenshot: David Zilkoski) — **Example of CSV Output Format Imported into Excel.** (Screenshot: David Zilkoski)

I stated in the xGeoid20 write up that the dynamic geoid model has also been updated this year in the form of xDGEOID20. This model is produced by NGS within the Geoid Monitoring Service (GeMS) and is part of the new NAPGD2022. For a thorough discussion on GeMS and the time-dependent geoid, view the webinar from NGS’ presentation library. See the box titled “GeMS Webinar by Kevin Ahlgren.”

GeMS Webinar by Kevin Ahlgren (available at https://www.ngs.noaa.gov/web/science_edu/presentations_library/). (Screenshot: David Zilkoski) — **GeMS Webinar by Kevin Ahlgren** (available at ngs.noaa.gov/web/science_edu/presentations_library). (Screenshot: David Zilkoski)

Also, one of my previous columns described NGS’ GeMS program. The images titled “Examples of the Time-Dependent Geoid Change in Alaska EPOCH 2020.0” and “Examples of the Time-Dependent Geoid Change in Alaska EPOCH 2025.0” show the change in geoid value from Epoch 2020 to Epoch 2025 for two stations in Alaska.

Examples of the Time-Dependent Geoid Change in Alaska EPOCH 2020.0. (Image: NGS) — **Examples of the Time-Dependent Geoid Change in Alaska EPOCH 2020.0.** (Image: NGS)

Examples of the Time-Dependent Geoid Change in Alaska, EPOCH 2025.0. (Image: NGS) — **Examples of the Time-Dependent Geoid Change in Alaska, EPOCH 2025.0.** (Image: NGS)

First, looking at the box titled “Examples of the Time-Dependent Geoid Change in Alaska EPOCH 2020.0,” the change between NAPGD2022 and NAVD 88 is approximately 1 meter. Users should note that the GEOID12B is used to establish the NAVD 88 height. Alaska was not included in GEOID18. Comparing the two Alaska labeled boxes, the xDGEOID2022 change between 2020.0 and 2025.0 is –4 mm. I will address this topic in more detail in future newsletters.

As stated by NGS news announcement, “The xGEOID models provide a preliminary but increasingly-accurate view of the changes expected from the upcoming North American-Pacific Geopotential Datum of 2022 (NAPGD2022).” NGS has produced many figures that describe the bias and trend between the future NADGP2022 and NAVD 88. In my June 2017 column I provided a plot that depicted the difference between NAPGD2022 and NAVD 88 based on the GPS on Bench Mark dataset. See the image below.

Figure from June 2017 Survey Scene column. (Image: NGS) — **Figure from June 2017 *Survey Scene* column.** Approximate Change Between NAPGD2022 and NAVD 88 Using GPS on BMs Data (units = cm). (Image: NGS)

These figures provide a broad picture of the change but to better understand the changes across the Nation, I used the GPS on Bench Mark dataset, that was involved in the creation of Geoid18 model, to compute an average latitude, longitude, and ellipsoid height for every State. Obviously, this is a fictitious mark but it provides an idea of the average change based on marks that have both a GNSS-derived ellipsoid and a leveling-derived orthometric height. The plot titled “Difference Between the Future NAPGD2022 and NAVD 88” depicts the average difference for each state based on the GPS on Bench Mark data file. These differences were generated using the xGeoid20B values from the output of the xGeoid20 website.

Difference Between the Future NAPGD2022 and NAVD 88. (Image: NGS) — **Difference Between the Future NAPGD2022 and NAVD 88.** (Image: NGS)

I would encourage everyone to select a couple of marks and compute the differences to understand the change in their particular region. I was the NAVD 88 Project Manager and I informed users of the potential changes between the NGVD 29 and NAVD 88 for about a decade, and I still had surveyors tell me that they didn’t know it was coming. Please take a few minutes to read NGS’ write up on xGEOID20, estimate the differences in your area of interest, and spread the word to your colleagues, friends, and clients.

The last item that I’d like to highlight is that NGS has released a beta version of a surface gravity model consistent with xGEOID20. See the box titled “Experimental Surface Gravity Model 2020 (xGRAV20).” Users can access the beta webtool here.

Experimental Surface Gravity Model 2020 (xGRAV20). (Image: NGS) — **Experimental Surface Gravity Model 2020 (xGRAV20).** (Image: NGS)

The access and input to the tool is similar to the xGEOID20 web tool. Saying that, I’d like highlight a few items:

The input height should be an orthometric type of height not an ellipsoid height.
If a height is entered, the tool will assume that is correct and use it for the gravity prediction.
If you do not know the elevation, leave the entry blank. The tool will use the DEM interpolated height if it is blank.

xGRAV20 Interactive Computation Page. (Image: NGS) — **xGRAV20 Interactive Computation Page.** (Image: NGS)

The box below provides the output using the tools sample data.

Output from Screen Output Format from xGRAV20 Tool. (Image: NGS) — **Output from Screen Output Format from xGRAV20 Tool.** (Image: NGS)

This gravity tool will be important when users want to incorporate leveling-derived orthometric heights into NAPGD2022. We will address this tool in more detail in future newsletters. I want to emphasis that these two web tools are beta sites. As a beta site, users should verify all information from the site. I encourage everyone to access the tool and check out a few of their favorite marks, and then send an email to NGS informing them of what you like, what you would like to change, and what you would like to see added to the tool.

NGS is releasing this tool as a beta product to get feedback from users. They are interested in your feedback concerning its function and usability as well as how users would like to interact with NGS web tools in the future. Email NGS at [email protected].

In conclusion, I want to leave you with a thought about change. When I give presentations and seminars, I usually include a slide that probably expresses the thoughts of many individuals.

My brother once told me:

“If you geodesists did it correctly the first time you wouldn’t have to keep performing adjustments and changing the values. Just do it right the first time.”

He’s a doctor and said he must do it right the first time.

My response to my brother and to everyone else is the following:

If you want to improve you have to be willing to change, and if you want to continue to meet future positioning requirements you need to continually change.

Winston Churchill said it better “To improve is to change; to be perfect is to change often.”

February 3, 2021

Brad Parkinson offers 5 ways to protect, improve PNT

What should the new administration’s priorities be to make PNT more resilient?

We asked Brad Parkinson, the “Father of GPS” and a GPS World Editorial Advisory Board member, what the new U.S. administration’s priorities should be to make positioning, navigation and timing (PNT) more resilient. For more answers from board members, see below.

Brad Parkinson

Protect the Spectrum. Reverse FCC authorization for relatively high-powered Ligado transmitters that have been proven to degrade GPS and other GNSS operation for thousands of PNT users. All U.S. government departments and major user groups affected have pleaded with the FCC to reverse this terrible decision. There is little benefit from it to the American public.

Protect the rapidly evaporating and self-proclaimed Gold Standard of GPS. The GPS satellite designs are showing their age. They need to go to multiple launch (three at a time) and revert to simpler designs without the spot-beams and other weighty add-ons that greatly increase complexity and cost. The Chinese have added to BeiDou (a) inter-satellite precision ranging and wide-band communications, (b) geosynchronous satellites, probably with good spot-beam acquisition aids, and (c) a WAAS-like correction directly on the satellites, which may have accuracies down to real-time kinematic (RTK, perhaps a few centimeters). Also, they claim their basic accuracies to be better than GPS (it might be true!) — I think they already have operational retro-reflectors.

Allow and encourage export of the basic and quickest fix to jamming and spoofing for high-value PNT users. More than 40 years ago, we demonstrated, in hardware, a high anti-jamming receiver that could fly directly over a 10 kW GPS jammer and not be affected. We know that high-gain, digital beam-steering antennas will create close to immunity, but our manufacturers will not move this way because we cannot sell or use them on the international market. These devices, combined with inexpensive inertial components and the newer signals, would make PNT virtually immune to current threats of interference — both jamming and spoofing.

Move the military focus from alternative PNT techniques to seriously upgrading their receivers and useful signals. No current or reasonably anticipated alternative can provide the accuracy (3D), availability or integrity of GPS. The new M-code and L1C signals have been in the queue for about 20 years. (Loran for ground operations probably is very vulnerable to direct attack in a fluid battlefield operation. Loran’s main value is to distribute time and for maritime users.) In those 20 years, we now have cellphone chips costing less than $5 that can listen to about 200 ranging signals and process RTK, as well as use all the corrections available (WAAS, EGNOS, etc.). Such capability cannot be found in military receivers. The Defense Department must improve its acquisition strategy in terms of both speed and competition, and ncorporate existing civil capability into military user equipment.

Take government actions to rapidly identify, shut down, and prosecute GPS jammers. Some believe this problem is much larger than recognized already. All cellphones should be required to report extraordinary spectrum noise levels or apparent attempts at spoofing. This should be fed to a dynamic national database, perhaps maintained by the Coast Guard. GPS users should have an automated way to find out whether there are substantial threats in their operating area.

Brad Parkinson is the Edward Wells Professor, Emeritus, Aeronautics and Astronautics (recalled) and co-director of the Stanford Center for Position, Navigation and Time at Stanford University.

Editorial Advisory Board PNT Q&A

Here are additional responses to the question from more GPS World Editorial Advisory Board members.

John Fischer

“We hope the new administration continues on the path established with the Executive Order last year for resilient PNT, supporting progress made by DHS and NIST in establishing resilient and cybersecure frameworks. It will be important for them to maintain an open market concept toward future innovative solutions and not mandate a particular PNT approach. Awareness of the criticality for trusted PNT in our mobile connected society is established and we must not lose this.”
John Fischer
Orolia

Jules McNeff

“Resilient PNT should be a national security priority. Its continuity is vital to both military and economic/social activities of all kinds. Its qualities of spatial awareness and synchronization enable the efficient functioning of the most sophisticated modern technologies in the physical and cyber worlds while also simply getting people and things from point A to point B on schedule. In that context, the elements which comprise resilient PNT should be protected from natural or hostile disruption.”
Jules McNeff
Overlook Systems Technologies

Greg Turetzky

“Truly resilient PNT requires combining multiple positioning technologies to maximize resiliency. However, the government’s influence in many of the augmentation technologies (sensors, vision, etc.) is limited. What the administration can do is make GPS itself more resilient by speeding up the launch and acquisition schedule of GPS Block III. The new signals, particularly at L5, are invaluable for improved resiliency to jamming and spoofing as well as providing a significant improvement in accuracy.”
Greg Turetzky
Consultant

February 1, 2021
Launchpad: GNSS chipsets, GIS software

A roundup of recent products in the GNSS and inertial positioning industry from the January 2021 issue of GPS World magazine.

OEM

Receiver board

Enhanced with corrections

Photo: Septentrio

The AsteRx-m3 Sx OEM board dual-antenna receiver combines Septentrio’s latest core GNSS technology with the SECORX-S sub-decimeter correction service to enable plug-and-play positioning. High-accuracy positioning is available directly out of the box, GNSS corrections automatically streamed to the receiver. This significantly simplifies the set-up process and eliminates the need for corrections service subscription and maintenance. Corrections are delivered via internet or L-band satellites, ensuring sub-decimeter service even in remote locations where there is no easy internet access.

Septentrio, septentrio.com

GNSS antenna

Smart antenna for 5G timing

Photo: Tallysman

The new TW5382 smart GNSS antenna is designed for high-accuracy 5G timing. The TW5382 is a multi-band, multi-constellation 5G smart GNSS antenna/receiver that provides 5 ns (1-sigma, clear sky view) timing accuracy. It consists of two components: a Tallysman GNSS Accutenna technology antenna and a professional-grade GNSS timing receiver module. Accutenna supports the full bandwidth of the TW5382 receiver, strong multipath mitigation and deep filtering in a compact IP69K enclosure. These features enable the antenna to provide a strong, pure, in-band, right-hand circular polarized signal to the receiver. The TW5382’s professional-grade multi-constellation and multi-signal timing receiver tracks GPS/QZSS (L1/L2), GLONASS (G1/G2), Galileo (E1/E5b), and BeiDou (B1/B2) signals.

Tallymatics, tallymatics.com

IoT GNSS module

For quick integration of precise positioning

Photo: Swift Navigation

The new Precision GNSS Module (PGM) is designed to offer fast evaluation and a quick path to production for those requiring a precise positioning solution. It is available in a simple-to-use, industry-standard mPCIe (mini peripheral component interconnect express) format and is designed specifically for Swift’s Starling positioning engine running on a host application processor to deliver real-time precision navigation. The PGM utilizes STMicroelectronics’ TeseoV chipset in Quectel’s multi-constellation, dual-band LG69T-AP receiver to create an affordable, easy-to-use solution for customers building industrial, last-mile and internet of things (IoT) platforms. This solution operates with the highest accuracy when used with Swift’s Skylark positioning service.

Swift Navigation, swiftnav.com

Inertial navigation system

Success in ultra-high-altitude flight simulation

Photo: Systron Donner

CAST Navigation tested Emcore’s SDN500 inertial navigation system (INS) in an ultra-high-altitude flight simulation and achieved success. The test required simulating performance at an altitude of more than 24,000 meters and velocities over 600 m/s. Only a few aircraft in the world have such capabilities, including the SR-71 Blackbird, but it is not practical to participate in a test flight on the SR-71. Simulating the SDN500 INS test flight to specific customer profiles on a CAST system is straightforward and cost-effective. Emcore relies on GNSS/INS simulators for hardware-in-the-loop testing to verify the expected performance of algorithms. Emcore sought to validate the velocity and altitude limits of a new GNSS receiver along with the algorithm performance in a tactical-grade SDN500 system.

Emcore, emcore.com
CAST Navigation, castnav.com

5G chipset

Ready for mass-market 5G phones

Photo: MediaTek

The Dimensity 700 5G smartphone chipset is a system on chip (SoC) designed to bring advanced 5G capabilities and experiences to the mass market. MediaTek’s Dimensity family of 5G chips is designed to give device makers a suite of options for 5G smartphone models. The chips range from flagship and premium to mid-range and mass market devices to make 5G more accessible for consumers everywhere. GNSS signals received include GPS L1CA and L5, BeiDou B1I and B2, GLONASS L1OF, Galileo E1 and E5, QZSS L1C and L5, and NavIC.

MediaTek, mediatek.com

UAV

Inspection software

For transmission towers

Photo: Cyberhawk

IHawk allows users to inspect sites remotely and then download and view the analysis anywhere in the world. It eliminates the need for engineers to climb towers for inspections or work in hazardous environments. The imagery and information gathered provides a detailed and highly accurate analysis of the condition of power transmission towers.

Cyberhawk, thecyberhawk.com

Heavy-lift UAV

System designed for Turkish rescue and security

Photo: UAVOS

The Alpin UAS is a long-range, heavy-lift unmanned helicopter capable of carrying up to 160 kg with a range of up to 840 km. The UAS includes a wideband satellite communication channel from its command-and-control station — a valuable feature, particularly for operations in remote areas. The Alpin unmanned helicopter is able to withstand severe weather conditions, carry multiple payloads, and transmit real-time information to defense forces and decision-makers in the field. Its system autopilot has features and advantages such as fully autonomous take-off and landing, remote ground-control network capability, auto-rotation landing capability and high efficiency flight control based on a total energy control system (TECS).

UAVOS, uavos.com

Metadata mapping

Secure web application enhanced for dji drones

Photo: Remote GeoSystems

LineVision Online now provides enhanced support for visualizing and mapping DJI drone video camera metadata and field-of-view projections. The secure web application is designed for immersive mapping, analysis, search, sharing and archive of geo-referenced videos, full-motion video, photos and other survey, inspection and surveillance datasets. With enhanced camera metadata mapping in LineVision Online, DJI drone videos can now display a dynamic, field-of-view outline representing where the gimbal camera was looking on the Earth as the video plays in the web-based map interface. Users can select any point along the UAV’s flight track on the map to immediately cue the video to play what was recorded at that location click point.

Remote GeoSystems, remotegeo.com

Agriculture drone

Comprehensive spraying system

Photo: DJI

The Agras T20 drone can conduct autonomous operations over a variety of terrains, such as broad-acre farmlands, terraces and orchards. As a comprehensive spraying system, the T20 allows users to easily set flight and operation parameters. With a built-in real-time kinematic (RTK) centimeter-level positioning system and RTK dongles, centimeter-level waypoint recording is enabled, strengthening operations and ensuring precision spraying.The T20 is equipped with eight nozzles and high-volume pumps that can spray at a rate of up to 6 liters per minute. A highly optimized wind field produces droplets of the correct size and consistency. The T20 is also equipped with a new four-channel electromagnetic flow meter, which monitors and controls four hoses individually, ensuring an efficient flow rate for each nozzle.

DJI, dji.com

SURVEYING AND MAPPING

Virtual base station

New feature in post-processing software

Photo: SBG Systems

A new virtual base station (VBS) feature is available in Qinertia, GNSS and inertial navigation system (INS) post-processing software. Trajectory and orientation are greatly improved by processing inertial data and raw GNSS observables in forward and backward directions. The VBS computes a virtual network around a project in which position accuracy is maximized, homogeneous and robust, such as a PPK short baseline. Once surveyors collect data, Qinertia chooses the most relevant reference stations, builds a virtual network and brings the project to centimeter-level accuracy with no convergence effects, even in urban areas.

SBG Systems, sbg-systems.com

3d data processing

Designed to decipher unstructured data

Photo: Enview

Enview Explore is a powerful web application that leverages artificial intelligence and cloud computing to automatically process 3D data at a high speed and scale. Enview performs a variety of geospatial operations, including object recognition, feature extraction, feature-based change detection, and 2D/3D measurement. Enview’s technology has been deployed on thousands of square miles worldwide to protect vital infrastructure and support mission-critical operations. Its unique method for classifying 3D data reduces time to action by focusing on finding meaningful insights.

Enview, enview.com

Pile installation

Machine-guidance system ready for solar

Photo: Carlson

PDGrade — a machine guidance and positioning system that uses GNSS for pile driving applications — is now optimized for the solar industry with an increased capability in pile installation and navigation accuracy. It removes the need for surveying piles and reviewing as-built information by centralizing all relevant information and providing necessary details to operators and site supervisors.The system features both software and hardware applications to provide operators with detailed information such as pile navigation, pile location, positioning and height information, project progression tracking, and detailed accuracy. The PD machine is fitted with Carlson sensors and a ruggedized Windows-based MC10 tablet. The entire system is then calibrated within PDGrade.

Carlson Software, carlsonsw.com

February 1, 2021
New 2-book set explores 21st-century PNT
By Jade Morton,
Guest Author

After more than five years of hard work by 131 authors from 18 countries, the new book set Position, Navigation, and Timing Technologies in the 21st Century (PNT21) is finally ready to meet readers.

Published by Wiley-IEEE Press, PNT21 offers a uniquely comprehensive coverage of the latest developments in the field of PNT by world-renowned experts. The two-volume set contains 64 chapters organized into six parts.

Position, Navigation, and Timing Technologies in the 21st Century
Integrated Satellite Navigation, Sensor Systems, and Civil Applications
Y. Jade Morton, Frank van Diggelen, James J. Spilker Jr. and Bradford W. Parkinson, editors; Sherman Lo and Grace Gao, associate editors
Publisher: Wiley-IEEE Press
Hardcover Publication Date: January 2021
Vol. 1: ISBN: 978-1-119-45841-8, 1288 Pages
Vol 2: ISBN: 978-1-119-45849-4, 912 Pages

Volume 1 focuses on satellite navigation systems, technologies, and applications. It starts with a historical perspective on GPS and other related PNT development.

Part A consists of 12 chapters on fundamentals of and latest developments in global and regional satellite navigation systems (GNSS and RNSS), the need for their coexistence and mutual benefits, signal quality monitoring, satellite orbit and time synchronization, and satellite- and ground-based augmentation systems that provide information to improve the accuracy of navigation solutions.

Part B contains 13 chapters on recent progress in satellite navigation receiver technologies such as vector processing, assisted and high sensitivity GNSS, precise point positioning (PPP) and real time kinematic (RTK) systems, direct position estimation techniques, and GNSS antennas and array signal processing. Also included are the challenges of multipath-rich urban environments, handling spoofing and interference, and ensuring PNT integrity.

Part C finishes the volume with eight chapters on satellite navigation for engineering and scientific applications. A review of global geodesy and reference frames sets the stage for discussions on the broad field of geodetic sciences, followed by a chapter on GNSS-based time and frequency distribution. One chapter each is dedicated to severe weather, ionospheric effects and hazardous event monitoring. Finally, comprehensive treatments of GNSS radio occultation and reflectometry are provided.

This simplified block diagram of a modern GNSS receiver — one of many illustrations in the book set — appears in Chapter 14, “Fundamentals and Overview of GNSS Receivers,” by Sanjeev Gunawardena and Y. Jade Morton. See excerpt below. (Image: Wiley-IEEE Press)

Volume 2 addresses PNT using alternative signals and sensors and integrated PNT technologies for consumer and commercial applications. An overview chapter provides the motivation and organization of the volume, followed by a chapter on nonlinear estimation methods which are often employed in navigation system modeling and sensor integration.

Part D provides seven chapters devoted to using various radio signals-of-opportunity transmitted from sources on the ground, from aircraft, or from low Earth orbit (LEO) satellites for PNT purposes.

In Part E, eight chapters cover a broad range of non-radio frequency sensors operating in passive and active modes to produce navigation solutions, including MEMS inertial sensors, advances in clock technologies, magnetometers, imaging, lidar, digital photogrammetry, and signals received from celestial bodies.

A tutorial-style chapter on GNSS/INS integration methods is included in Part E. Also included are chapters on the neuroscience of navigation and animal navigation.

Finally, Part F presents a collection of contemporary PNT applications such as surveying and mobile mapping, precision agriculture, wearable systems, automated driving, train control, commercial unmanned aircraft systems, aviation, satellite orbit determination and formation flying, and navigation in the unique Arctic environment.

Table of Contents

Volume 1: Satellite Navigation Systems, Technologies, and Applications
- Part A: Satellite Navigation Systems
- Part B: Satellite Navigation Technologies
- Part C: Satellite Navigation for Engineering and Scientific Applications
Volume 2: Integrated Navigation Systems, Technologies, and Applications
- Part D: Position, Navigation, and Timing Using Radio Signals-of-Opportunity
- Part E: Position, Navigation, and Timing Using Non-Radio Signals-of-Opportunity
- Part F: Position, Navigation, and Timing for Consumer and Commercial Applications
Collective Goal. Because of the diverse authorship and topics covered in PNT21, the chapters were written in a variety of styles. Some offer high-level reviews of progress in specific subject areas, while others are tutorials. A few chapters include links to MatLab or Python example code as well as test data for readers who desire hands-on practice.

The collective goal is to appeal to industry professionals, researchers and academics involved with the science, engineering and application of PNT technologies. The website pnt21book.com provides downloadable code examples, data, homework problems, select high-resolution figures, errata and a way for readers to provide feedback.
Jade Morton is a professor at the University of Colorado Boulder and director of the Colorado Center for Astrodynamics Research (CCAR).

Jade Morton is a professor at the University of Colorado Boulder and director of the Colorado Center for Astrodynamics Research (CCAR).

Excerpt from PNT21

14.1 Anatomy of a GNSS Receiver

Irrespective of the receiver type, the functionality of all GNSS receivers can be broken down into three major blocks: RFFE, baseband processor (BBP), and system processor (SP). In the literature, the term “baseband processor” may be used to refer to the combination of both the BBP and SP defined here. The general anatomy of a GNSS receiver is shown in Figure 14.3.

The RFFE converts the signals induced at one or more antennas into digitized sample streams. Depending on the application and market segment, data rates for these streams may be as low as 0.4 Mbytes/s (e.g. L1 band sampled at 3.5 MSPS and 1-bit sampling in an asset tracking device) to greater than 3 GB/s (e.g. L1 and L2 bands sampled at 60 MSPS and 16 bits across seven elements in an anti-jam military GPS receiver).

The BBP performs digital signal processing to acquire and track GNSS signals present in the digitized sample streams to produce raw GNSS observables for each visible satellite. These observables include time of transmission (TOT), accumulated Doppler Range (ADR), signal quality metrics such as carrier-to-noise density ratio (C/N0), in-phase and quadrature prompt correlator output (I/Q), and raw symbols of a GNSS signal’s broadcast navigation message (which are subsequently decoded). In addition, modern receivers typically perform varying degrees of situational awareness processing to monitor in-band interference such that a level of confidence can be assigned to these raw observables. Some advanced receivers have the ability to identify spoofing signals. Depending on the application, situational awareness outputs may be as rudimentary as the automatic gain control (AGC) voltage used to adjust front-end amplification or as sophisticated as spectrogram, histogram, and sample statistics for all streams evaluated at full sample precision.

The BBP also contains a counter that is driven by a digital clock signal that is phase-locked to the receiver’s reference oscillator. This counter is the basis for the receiver’s clock and is used to generate time-of-reception (TOR) epochs. Raw observables for all satellites in view that lead to range measurements are computed with respect to TOR epochs. Since the receiver clock is based on its reference oscillator, it drifts with respect to GNSS system times. Although possible, the frequency bias, drift, and drift rate of the reference oscillator are typically not adjusted to align with GNSS system time because dynamic adjustment of the oscillator can lead to instabilities. Instead, these parameters are estimated and used to drive a separate adjustable-rate counter that compensates for the reference oscillator errors. This forms the basis for GNSS disciplined oscillators.

It is possible to partition all baseband processing into two categories: sample processor (SMP) and reduced-data processor (RDP). The SMP performs high-rate but simple and algorithmically regular operations which largely comprise multiply-accumulate operations performed at the sample rate. The SMP may also contain configurable timers and pulse/event generators that determine sample processing intervals, as well as output precise timing pulses that are synchronized down to the nanosecond level with respect to GNSS system times (timing accuracy and precision are dependent on the application and market segment). The RDP performs low-rate but algorithmically complex operations. Some representative software functions running within the RDP are illustrated in Figure 14.3.

Bidirectional communications occur between the SMP and RDP at regular timed intervals corresponding to a kilohertz rate. This rate is easily handled by all modern microprocessors. Since these SMP/RDP transactions are time critical, the RDP runs either bare-metal code (i.e. no operating system) or a real-time operating system. The operations within the BBP are inherently parallel and largely independent of each other at the signal processing level. Some coupling occurs, for example‚ in code-carrier aiding, inter-frequency aiding (see Chapter 15), inter-satellite aiding (referred to as vector tracking, described in Chapter 16), and multi-element processing. However, this coupling is typically implemented at higher levels of abstraction. Modern multi-band and multi-constellation receivers are capable of tracking hundreds of GNSS signals simultaneously. To facilitate this highly complex command and control structure – which also needs to be dynamically scalable and adaptive depending on the number of satellites in view, environmental conditions‚ and operating modes – the control architecture is typically layered (i.e. hierarchical). Control at the individual signal acquisition and tracking layers is performed using simple configurable finite state machines (FSMs) whose state transitions are based on signal condition indicators such as code lock, phase lock, C/N0, and code-carrier divergence (CCD). These FSMs operate independently but are typically managed at a high level by the SP.

The SP takes the raw signal observables produced by the BBP and transforms them to the standard GNSS receiver measurements. These measurements include pseudorange (PR), accumulated Doppler range (ADR), carrier phase (CP), carrier Doppler, and C/N0. All modern GNSS receivers also compute position, velocity, and time (PVT) at configurable rates (1 to 100 Hz depending on the receiver type). The SP encodes these in one or more industry-standard data formats for distribution. These formats include Receiver Independent Exchange Format (RINEX), the National Marine Electronics Association (NMEA) format, the Radio Technical Commission for Maritime Services (RTCM) format, and vendor-specific proprietary binary formats.

The SP also performs all high-level functions that include receiver initialization, channel management, and user interface functions. Unlike the BBP, the operations within the SP are generally not time critical. In modern GNSS receivers, the SP is often an embedded computer running an advanced non-real-time operating system. It may also support modern data interfaces (wired USB and Ethernet, or wireless/cellular connectivity) and an advanced graphical user interface with touchscreen support. While too numerous to mention, representative software processes running within the SP are illustrated in Figure 14.3.

Although not shown in Figure 14.3, modern receivers (or the navigation system to which they are interfaced) may also support aiding from external sensors such as inertial measurement units (IMUs), magnetometers, inclinometers, barometers, wheel sensors, RADAR, lidar, infrared (IR), and electro-optical (EO) sensors. This external aiding to GNSS can occur at three levels: loose coupling (position level), tight coupling (measurement level), or ultra-tight coupling (sampled signal processing level). GNSS aiding using various non-GNSS sensors is described in Chapters 43–51 in Volume II, Part E.

As shown in Figure 14.3, a stand-alone GNSS receiver contains battery-powered low-power circuitry to keep track of absolute time while it is turned off. A real-time clock (RTC) driven by a low-power crystal oscillator accomplishes this task. In some cases, this crystal may be the same as the reference oscillator. Knowledge of absolute time, along with the last known location and previously decoded almanac/ephemeris data stored in the receiver’s non-volatile memory, allows it to estimate satellites in view and their Doppler offsets, thereby significantly reducing the TTFF: the time needed to acquire satellites and produce the initial PVT solution. In the case of modern military receivers such as M-Code, or subscription-based services such as the Galileo Public Regulated Service (PRS), the receiver must acquire the cryptographically generated spreading code that may never repeat. In this case, the initial time uncertainty has a significant impact on the acquisition search space and consequently the computational resources consumed by the acquisition engine as well as power consumption. The TTFF can be dramatically reduced when absolute time, the satellites in view, their Doppler frequencies, and ephemerides are sent to the receiver from a nearby reference station via a communications link. This describes the basis of Assisted GNSS (A-GNSS) technology, covered in Chapter 17 of this book.

In some respects, the reference oscillator can be considered the single most important component that affects GNSS receiver performance. Although the PVT solution estimates the deterministic components of the reference oscillator’s frequency error (i.e. short-term bias, drift, and drift rate), the stochastic component cannot be estimated and hence represents additional dynamics that must be tracked (i.e. in addition to satellite motion, user motion, satellite clock motion, and any ionospheric scintillation and multipath). The bandwidth of the carrier tracking loops must be increased to accommodate this close-in phase noise of the reference oscillator. This in turn increases the variance of the range measurements. The reference oscillator is also the only “moving part” in the receiver since it is based on the resonance of a quartz crystal or microelectromechanical systems (MEMS) structure. In addition to microphonics, which are small phase variations that may occur within the RFFE due to external forces (particularly if the RFFE comprises large discrete components), these forces couple through the resonating element leading to shock and vibration sensitivity [6]. Similarly, thermal expansion of the crystal as well as analog components in the RFFE due to changing ambient temperature, unless appropriately compensated or isolated, causes temperature sensitivity. The frequency synthesizer in the RFFE multiplies the oscillator phase noise and dynamics by the ratio of the synthesizer output frequency to the oscillator fundamental frequency, thus placing a significant short-term stability requirement on the reference oscillator. Oscillator short-term stability limits the coherent integration time, which is proportional to the processing gain. Hence, the quality of the reference oscillator directly impacts the recever’s attainable sensitivity (i.e. the minimum observable signal levels) as well as the rate at which it can output statistically independent measurements. Oscillator effects are covered in detail in Chapter 47.

The receiver intelligence process within the SP shown in Figure 14.3 performs functions such as determining what satellites are in view, how best to mitigate any in-band interference (as observed by the situational awareness indicators), dynamically adapting to varying operating conditions, determining the best set of range measurements to use for the PVT solution based on optimum satellite geometry and estimated range error metrics indicated by C/N0 (for signal blockage) and CCD fluctuations (for multipath and ionospheric effects), and many such highly complex decisions. Typically, these high-level functions occur at a lower rate such as 1 Hz or less. To a large degree, the level of sophistication and engineering embedded within the receiver intelligence block, as well as the other low-level control functions determines the receiver’s performance in the real world, as expressed by established figures of merit. These include measurement accuracy, update rate, TTFF, sensitivity, dynamics handling capability, multipath mitigation performance, interference detection and mitigation capability, receiver autonomous integrity monitoring, and fault detection and exclusion (see Chapter 23). In other words, for a given market segment and its associated SWaP-C constraints, the receiver’s hardware and available signal processing capabilities can only do so much. The rest, and quite often the attributes that distinguish it in the marketplace, lies within the hundreds of thousands of person-hours and centuries of combined experience baked into its sophisticated software/firmware.
February 1, 2021
Editorial Advisory Board PNT Q&A: PPP versus RTK

Every month, we ask members of our Editorial Advisory Board to weigh in on a topic. For the January 2021 issue, we asked,

Will precise point positioning (PPP) replace real-time kinematic (RTK)? If so, for which applications and when?

Miguel Amor

“Recently, Hexagon’s Autonomy & Positioning division demonstrated RTK levels of performance — globally —through PPP technology; we call it RTK From the Sky (see page 29). I believe that PPP adoption rates will grow significantly in the coming years and eventually replace RTK — especially in areas that are not well served by RTK networks or similar services. Adoption rates will depend on which applications can field GNSS receivers capable of the signals and constellations to perform like RTK.”

Miguel Amor
Hexagon’s Autonomy & Positioning division

Alison Brown

“For many applications, the improved accuracy provided by PPP (10 cm) is sufficient and RTK solutions are not needed. However, the typical convergence time of PPP is between 20 and 40 minutes, depending on the number of satellites available, satellite geometry, the quality of the correction products, the receiver’s multipath environment, and atmospheric conditions. This slow convergence compared to RTK solutions will limit application for many real-time applications such as mobile solutions.”

Alison Brown
NAVSYS Corporation

Jean-Marie Sleewaegen

“PPP-RTK combines near-RTK accuracy and quick initialization times with the broadcast nature of PPP, over internet or L-band. PPP-RTK can be seamlessly integrated into GNSS receivers, bringing convenient sub-decimeter accuracy to applications where configuring RTK is not practical or where there is no internet connection. PPP-RTK is likely to be adopted by emerging mass-market applications such as UAVs, while RTK will probably remain prevalent in applications where it is already well established, such as precision agriculture.”

Jean-Marie Sleewaegen
Septentrio

Bernard Gruber

“I do not believe that PPP will replace RTK technology solutions anytime soon. Satellite-based GNSS correction services with an emphasis on global provide worldwide access, but achieving the required accuracy, due to convergence, can be slow. Today, myriad users and emerging customers may utilize corrections augmented with RTK transmitter/base stations that hybrid solutions can provide, thus solving both the age-old navigation issue of obscuration and near real-time positioning simultaneously.”

Bernard Gruber
Northrop Grumman

January 31, 2021
Why geospatial data needs artificial intelligence

By San Gunawardana, Guest Author

Advances in geospatial technology have opened up many new possibilities in areas such as national security, urban planning and emergency preparedness. When I was embedded with the U.S. Army as a scientist in Afghanistan, I got to experience firsthand the exceptional value of 3D data. The military used nation-scale imagery and lidar to generate 3D maps that then informed their safety-critical operations. However, since lidar—like most three-dimensional unstructured data—contains incredible complexity and detail, it was painfully slow to analyze manually.

As a result, the impact of this technology was severely restricted by speed and cost due to the significant manual effort required to extract actionable insights. As we looked to the future, where lidar would become commonplace in consumer electronics and automobiles, it became clear that there was an opportunity to combine computer vision/AI with large-scale cloud computing to rapidly and automatically generate actionable insights from 3D data.

Screenshot: Enview

After returning from Afghanistan, I reconnected with Krassimir Piperkov, a former colleague from ICON Aircraft, and fellow Stanford alum, to launch Enview. Our objective was to automate 3D geospatial analytics and create a living 3D model of the world to help organizations to protect their critical infrastructure and communities.

Powering geospatial data with AI can take the limits off 3D data analytics, prevent threats from becoming incidents, and protect critical infrastructure. What used to take days or months to process can now be done in minutes, enabling analysts, operators, and decision-makers across the public sector to make timely and accurate decisions. By enhancing our understanding of the physical world, this technology empowers us to tackle pressing challenges like wildfire prevention, humanitarian assistance, disaster response, and more.

Let’s take a look at how AI-powered 3D modeling is being put to use.

Digital twins

A living 3D model of the world, or a digital twin, can be used for many purposes. Enview’s software fuses many different data sets together to create digital twins that are global in scale but have high-resolution to enable local decision-making. These digital twins include 3D terrain, vegetation, buildings, and infrastructure such as power lines, roads, and water works. Enview also fuses real-time and forecasted conditions, such as wind, temperature, humidity, traffic, and IoT (internet of things).

This sort of rich representation of the physical world is an incredibly complex big data challenge. Data comes from radically different sensor modalities, with different resolutions, formats, time-domains, and accuracy. AI plays a critical role in automating the fusion of these datasets, by helping to intelligently align and then fuse them into a cohesive entity. 3D geospatial data is particularly challenging, as it is unstructured data, which requires a new generation of deep learning frameworks whose convolutional kernels are specifically developed from the ground up to work on unstructured data. Further, the datasets are massive in scale. A square-mile of 3D lidar data can have hundreds of millions of points; the magnitude of the data easily passes the petabyte scale when one considers applications that span nation-scale areas. In order to process this volume of data, modern geospatial AI architectures must be containerized and dynamically deployable across cloud compute resources to generate timely insights.

AI is essential to help human experts to extract meaningful insight from this overabundance of data. The application of automated workflows allows experts to look at larger areas, with more speed and higher frequencies. This machine-assisted cognition draws upon the respective strengths of people and computers to do what neither could do on their own.

Humanitarian aid and disaster relief

3D models can be built to monitor hurricane hotspots, such as the Gulf Coast, before major storms strike. By layering in real-time weather information such as rainfall, winds, and flooding, these models can help with planning, emergency response, and relief efforts.

This data also provides life-saving insight that can assess damage to buildings, transportation, and downed power lines, in addition to determining where to send medical and relief supplies, and how to best get them there. 3D data can help to lessen the impact of future weather events by updating the baseline understanding of how storms impact coastal communities so they can plan for the future.

Screenshot: Enview

Infrastructure protection

Inadequate clearances between vegetation and power lines can result in wildfires and unplanned power outages. Many federal, state, and local regulations are in place to mandate clearances, and power line operators monitor their networks continuously to ensure that they abide by these regulations and prevent incidents and outages. However, doing so by walking or flying the lines and judging distances with the human eye is challenging and inaccurate.

The ability to identify the exact location and clearances of high-risk vegetation early, and at scale, lets operators identify, prioritize, and address problem areas proactively. Lidar-driven programs have helped with risk-reduction, but are constrained by the massive levels of manual data manipulation required to derive insights from this 3D data. The automation of 3D geospatial analytics through AI, machine vision, and parallel computing enables the accurate and rapid identification of at-risk areas, protecting critical infrastructure and communities.

Screenshot: Enview

Fighting wildfires

Devastating wildfires resulting in the loss of life and property have become commonplace in the western U.S. and other parts of the world. The tools and methods previously relied on to keep communities and infrastructure safe are now struggling to keep up with this increased threat.

Geospatial information, including 3D data, provides a digital view of the physical world and, when paired with AI, gives stakeholders the informational edge they need to minimize wildfire damage, injuries, and deaths. This technology can be used to automatically build and update real-time, high-resolution wildfire risk maps that give firefighters and communities more notice when threats are imminent, and provide firefighters with real-time situational awareness when they’re fighting the blazes.

Change detection

According to the Pipeline and Hazardous Materials Safety Administration (PHSMA), third-party excavations are one of the leading causes of pipeline incidents in the U.S. These incidents can lead to service disruptions, expensive repairs, and sometimes serious injuries or deaths.

Detecting signs of excavation or earth movement via aerial patrolling is challenging and costly, while resource limitations make it difficult for pipeline operators to continuously monitor remote areas such as farms. AI-powered 3D maps can be used to monitor topography and accurately detect changes that threaten pipelines in real time.

3D data provides remarkable value when it comes to decision-making as it relates to many different applications—from military defense to protecting neighborhoods from wildfires. However, its success hinges on one thing: speed. The ability to process 3D geospatial data rapidly, and at scale, is made possible through advances in AI and cloud computing. In the future, we can expect to see more exciting and innovative use cases for AI-powered geospatial technology.

San Gunawardana is co-founder and CEO of Enview, a geospatial analytics company. After finishing a Ph.D. in aerospace engineering at Stanford, Gunawardana went to Afghanistan, where he combined data analytics and remote sensing to detect threats and prevent incidents. He is excited to apply those insights to help the energy sector solve problems. He has done computer vision at NASA, built imaging satellites with the Air Force, and was an early employee at ICON Aircraft.

January 27, 2021
GNSS Winter School set to take place in Islamabad

GNSS Winter School 2021 is planned for Feb. 22-26 in Islamabad, Pakistan. The Institute of Space Technology is hosting the event, in collaboration with the Space Education Research Lab of the National Center of GIS and Space Applications.

GNSS Winter School will be held on the institute’s campus; however, in case of severe circumstances (such as COVID-19), it will take place virtually online either partially or entirely.

GNSS Winter School will focus on GNSS positioning, coordinate and time reference systems, satellite orbit and position determination, signals, receivers, and specialized areas of inertial and integrated navigation systems.

A special session is planned on GNSS applications and opportunities in the current GNSS market.

The school is intended for engineers, researchers and students working in aeronautics and astronautics; guidance, navigation and controls; satellite or radio navigation; inertial and integrated navigation systems; space systems; constellation designs; interplanetary navigation; remote sensing; geoinformation science; and similar allied areas.

Registration is open through Feb. 15.

January 26, 2021
New GNSS receiver front-end integrates, simplifies

Photo: STMicroelectronics

STMicroelectronics’ latest RF front-end for GNSS receivers offers a simplified design and smaller footprint. The BPF8089-01SC6 integrates the impedance-matching and electrostatic discharge (ESD) protection circuitry typically implemented using discrete components.

The BPF8089-01SC6 provides a 50-ohm matched interface between the receiver’s antenna and low-noise amplifier (LNA), and is ready for plug-and-play with the company’s STA8089 and STA8090 LNAs.

The BPF8089-01SC6 is suitable for use in portable receivers for the GPS, Galileo, GLONASS, BeiDou and QZSS constellations, which can be used in applications such as consumer satellite navigation, radio base stations, drones and tracking of assets or livestock.

The BPF8089-01SC6’s compact, integrated front-end can replace a matching network containing up to five capacitors, resistors and inductors, as well as two discrete protection devices, resulting in a much smaller footprint. Designers can also leverage PCB-track specifications provided in the device datasheet to ease design challenges and ensure optimal performance.

The ESD protection provided complies with IEC 61000-4-2 (C = 150 pF, R = 330 ohm) and exceeds level 4: 8 kV for contact discharge and 15 kV for air discharge. The device also withstands 2 kV pulse voltage in accordance with MIL-STD 883 C (C = 100 pF, R = 1.5k ohm).

Part of ST’s Application Specific Integrated Passives (ASIP) product range, the BPF8089-01SC6 is housed in a SOT23-6L package compatible with automatic optical inspection.

January 26, 2021
James Litton, GPS and precision ag pioneer, dies

James Litton

James D. Litton, GPS pioneer and founder of NavCom Technology Inc., died over the weekend at his home in California with his family at his side. He was 89 years old.

Litton was an early contributor to the development of GPS user equipment. He also played a pivotal role in the GPS-driven transformation of global agriculture that has greatly benefited humanity.

Litton was the director of engineering at Magnavox Research Labs when researchers were working on using CDMA for range measurements, a precursor to the GPS system. He also worked on the original proposal for GPS Phase I.

Later, as general manager of Magnavox’s Marine and Survey Systems Division, he helped develop new and advanced commercial navigation and survey receivers for both the Navy’s TRANSIT system and the Air Force’s GPS.

His team developed the first microprocessor-based commercial satellite navigation receivers and the first commercial GPS survey software. This led to Magnavox eventually having more than a 90 percent share of the survey receiver market.
The firm eventually held more than two dozen patents for improvements in GPS technology.

In 1992, Litton left Magnavox to start a consulting business. Two years later, with Ron Hatch, K.T. Woo and Jalal Alisobhani, he founded NavCom Technology Inc. With Litton as CEO, NavCom became a significant player in the GPS marketplace. Among its achievements was development — under contract — of a single-frequency WAAS-capable GPS aircraft navigation receiver.

NavCom also began a relationship with Deere & Company, supporting more efficient and productive agriculture. This relationship was so successful that Deere purchased NavCom in 1999. Litton continued to lead the company and serve as part of Deere’s senior management team for eight more years.

In recognition of his many achievements to the field, Jim Litton was presented the Institute of Navigation’s Hays Award in 2006.

Among his many contributions, his impact on global agriculture might well have been his greatest, according to Brad Parkinson, the original chief architect for GPS.

“His work transformed agriculture into a data-driven, technological industry that was incredibly more efficient,” Parkinson said. “The cost savings and increases in productivity have impacted billions around the world.”

Jim’s family has created a memorial fund at Doctors Without Borders for those wishing to make a donation in honor of his life and many good works. Click here.

January 26, 2021
Contracts awarded for next-generation Galileo satellites

Image: ESA

The European Commission has issued industrial contracts worth €1.47 billion ($1.97 billion) to build next-generation Galileo satellites to Airbus and Thales Alenia Space, reports BBC News.

Both companies told BBC News that they will not speak publicly about their contracts wins until documents are signed, which could take several weeks.

Read more about Galileo and its plans in Directions 2021: Galileo expands and modernizes global PNT by Javier Benedicto and Rodrigo da Costa.

Each contract is for manufacture of six satellites, to orbit no earlier than 2024. They will feature digitally configurable antennas, inter-satellite links, new atomic clocks and propulsion systems that use electric engines.

Airbus and TAS built the four Pathfinder in-orbit validation satellites that first demonstrated Galileo. A consortium of OHB-System and Surrey Satellite Technology Ltd. built the first operational Galileo satellites, but the consortium ended following Brexit.

January 26, 2021
University revises PNT backgrounder In response to concerns

Beyond GPS report. Check out the report here. (Cover: NSI)

George Mason University has revised a briefing paper on positioning, navigation and timing (PNT) in response to concerns about its accuracy.

The university’s National Security Institute “NSI Backgrounder — Beyond GPS: The Frontier of Positioning, Navigation, and Timing Services” was first issued on Dec. 2. Some staff on Capitol Hill and members of industry soon had concerns about several of its assertions.

Responding to letters from industry, National Security Institute (NSI) Executive Director and Professor Jamil Jaffer said he determined that three of the issues raised, while not fatal to the document, warranted clarification.

ELoran callout. The first was a statement in the backgrounder that the National Timing Resilience and Security Act (NTRSA) “specifies 13 technical requirements for a GPS backup, which essentially define the eLoran system.”

This was a concern to some on the hill as Congress is generally reluctant to specify solutions. Legislators prefer to specify outcomes and then defer to the executive branch on how to make them happen.

Members of industry pointed out that government systems like WWVB and the low-frequency portion of DARPA’s STOIC program, as well as commercial systems like NextNav and Locata, could meet or be adapted to meet the NTRSA requirement.

The revised backgrounder says the NTRSA “specifies 13 mainly technical requirements for a GPS back-up, which align closely with the capabilities of the eLoran system. Other systems may meet the Act’s requirements to varying degrees.”

Multiple technologies. The revised backgrounder also corrects a statement that the NTRSA requires the Department of Transportation to establish an eLoran system. It now says “a system that complies with the Act, and DOT may pursue multiple technologies in implementing the Act.”

Department officials had previously said they were taking a system-of-systems approach and expected to employ multiple technologies. Subsequently, a DOT report was released that documents the need for several diverse systems. It lists transmissions using low frequency (eLoran, STOIC), ultra high frequency (NextNav, Locata) and L-band from space (GPS, Satelles). It also says the terrestrial transmitters should be interconnected by fiber.

Public-private partnership. A third correction was made in the document to reflect how the Congressional Budget Office regarded the possibility of using a public-private partnership in previously proposed legislation.

Members of industry also expressed concern that one of the authors of the document serves on the advisory board for Satelles Inc. and that this was not disclosed in the paper. The backgrounder appeared on the Satelles website the same day it was published.

The university concluded that such disclosure was not necessary as the paper said the author “provides advisory services to industry, including in the PNT area.” At the author’s request, though, his profile on NSI’s webpage will be updated to show his relationship with Satelles.

January 26, 2021
2021 Defense Act signals turning point for Congress and PNT
Photo: Toshe_O/iStock / Getty Images Plus/Getty Images

Senate joined House to override Trump’s veto, making bill into law

The U. S. Congress, especially the Armed Services Committees, have long been concerned about GPS and positioning, navigation and timing (PNT) issues. Over the past two decades, Congressional hearings, demands for reports and investigations have dealt with acquisition, contingency plans for when space is not available, deliberate interference, and a host of other issues.

While these all evidenced Congress’ interest and concern, they were relatively passive measures.

This began to change in 2018 with passage of the National Timing Resilience and Security Act. It requires the Department of Transportation to establish a terrestrial timing system to backup GPS signals.

Then in 2019, Congress appropriated money for a GPS Backup Technology Demonstration. And the National Defense Authorization Act (NDAA) for 2020 required the Air Force to develop a prototype multi-GNSS receiver as part of its resiliency efforts.

The NDAA for 2021 seems to finalize Congress’ transition from an interested observer, mostly on the sidelines, to an active player in national PNT issues and policy.

GPS Under Threat

Capitol Hill observers say this is the result of several factors that have come to a head over the last year. Taken together, they have convinced many legislators that GPS is under threat and PNT issues are not being taken seriously enough by the executive branch. These include increased jamming and spoofing (especially by China and Russia), full implementation of China’s BeiDou system and its marketing to other nations as a superior alternative to GPS, the Federal Communications Commission’s (FCC) decision on Ligado Networks, and the Pentagon’s failure to respond to combatant commanders’ Joint Urgent Operational Needs Statements for non-GPS PNT.

Here are some of the provisions of the 2021 NDAA of interest to the PNT community.

Military Multi-GNSS Prototype

The 2018 NDAA required the Defense Department to incorporate Europe’s Galileo and Japan’s QZSS satellite navigation signals into military user equipment. The idea was to make it more resilient to disruption. Also required was an investigation into using non-allied signals.

Apparently not satisfied with progress on this project, Congress mandated a project to develop a prototype multi-GNSS receiver as part of the 2020 NDAA.

The 2021 NDAA seems to indicate Congress is still not happy. It withholds 20% of the funding for the Office of the Secretary of the Air Force until the department certifies the prototype project is underway and provides briefings to the Senate and House Armed Services Committees.

Resilient, Survivable PNT

Language in the 2021 NDAA also seems to show Congress is impatient with the Pentagon’s lack of responsiveness to combatant commanders’ requests for non-GPS PNT systems.

Section 1611 of the act is entitled “Resilient and Survivable Positioning, Navigation, and Timing Capabilities.” It requires development, integration and deployment of these capabilities for combatant commanders within two years. This, it says, is “… consistent with the timescale applicable to joint urgent operational needs statements…”

The act says the new PNT capabilities shall “generate resilient and survivable alternative positioning, navigation, and timing signals” and “process resilient survivable data provided by signals of opportunity and on-board sensor systems…”

The act also addresses the Defense Department’s 2018 PNT Strategy’s plan for future systems to be classified and for military use only. It directs the department to work with the National Security Council, Departments of Transportation, Homeland Security and others “…to enable civilian and commercial adoption of technologies and capabilities for resilient and survivable alternative positioning, navigation, and timing capabilities to complement the global positioning system.”

To help ensure prompt action on this, the act requires a report to Congress within six months and authorizes the department to reprogram funds from other areas to finance the effort.

Responding to Ligado Decision

By far the most PNT-related text in the 2021 NDAA includes a host of measures responding to FCC Order 20-48 approving an application by Ligado Networks. An order that the executive branch is on record as strongly opposing, saying it will degrade GPS service for many.

Senator Jim Inhofe, chair of the Senate Armed Services Committee, has regularly expressed outrage at the FCC’s decision and has called for its reversal.

Among its provisions, the act:
- requires the Department of Defense to estimate and report to Congress the cost of damage to department systems as a result of the FCC order.
- prohibits using department funds to upgrade or modify military equipment to make it resilient to interference caused by broadcasts in the spectrum allocated (the FCC order requires this to be funded by Ligado).
- prohibits contracting with any entity using the frequency bands allocated to Ligado unless the Secretary of Defense certifies the use will not interfere with GPS services.
- requires the Secretary of Defense to contract with the National Academies of Sciences, Engineering, and Medicine for an independent technical review of the FCC order.
Dana Goward is president of the Resilient Navigation and Timing Foundation (rntfnd.org).
January 25, 2021