Tweet a selfie with @GPSWorld Group Publisher and Editor-in-Chief Alan Cameron OR in the GPS World booth at ION GNSS+ and you will be entered to win two tickets to the GPS World Leadership Dinner!
To qualify, simply tweet a selfie with @gpseditor Alan Cameron, or in the GPS World booth, tag @GPSWorld and use #iFoundAlan. One winner will be randomly selected at 1 p.m. on Thursday, Sept. 28, and contacted via direct message on Twitter. Photo must be taken at ION GNSS+ 2017 and submitted prior to noon on Sept. 28.
LTE chipmaker Sequans Communications S.A. and semiconductor company STMicroelectronics have introduced CLOE, an LTE-connected tracker platform based on the integration of Sequans and ST technologies.
An acronym of Connecting and Locating Objects Everywhere, CLOE combines the Internet-of-Things (IoT) technologies of two industry manufacturers into one comprehensive platform that simplifies the development of LTE-based IoT tracker devices for the full range of vertical markets, including logistics, consumer electronics and automotive.
Specifically designed and optimized for OEMs and ODMs to add IoT tracking capability to their product offerings, CLOE integrates Sequans’ Monarch LTE Cat M1/NB1 chip and ST’s Teseo III GNSS chip for communications and satellite-based tracking performance.
“CLOE targets multiple vertical markets with best-in-class performance for all of the important tracking measures: battery life, location accuracy, reachability, mobility and reporting periodicity,” said Antonio Radaelli, infotainment BU director at STMicroelectronics. “’Componentizing’ ST’s navigation technology and Sequans’ LTE modem technology makes CLOE an ideal platform to build trackers of all types — anything a developer can think of.”
“The tight integration of ST’s latest-generation Teseo chip with our Monarch LTE chip results in a power-optimized, cost-effective, all-in-one solution to speed new IoT tracker devices to market in a very short time,” said Danny Kedar, vice president of Sequans’ IoT business unit. “CLOE delivers ultra reliable LTE connectivity with ultra-low-power consumption, and high performance GNSS and accelerometer performance, including lowest time to first fix.”
CLOE Key Features
Turnkey cellular tracker solution for OEMs and ODMs, anywhere in the world
Chipset integrates PMU, LTE, GNSS, memories and MCU
First-to-market, operator-certified
LTE Cat M1/NB1 dual-category
Covers all worldwide LTE bands with a single hardware design
High GNSS accuracy and short time to first fix
Support for autonomous or server-based Assisted GPS (AGPS) for optimal time to fix
Designed to address multiple track & trace segments, including
Logistics
Consumer electronics
Automotive
Optimized for low power consumption and cost
Modular design includes GNSS, cellular connectivity, MEMS; can be expanded to include other sensors, Bluetooth and/or Wi-Fi.
CLOE is designed and optimized for production based on a full bill of materials (BOM) that includes LTE, GNSS, accelerometer, power supply, battery management, LED and button management. The modular design enables copy/paste and optimizes BOM cost. CLOE is easily customizable.
In Portland, Oregon, and in Berlin, Germany, the two largest and most important international conferences on GPS, GNSS, PNT, survey, mapping and geodesy take place this year on exactly the same dates — just 5,177 miles apart. Now that’s bad timing. Our strategy is to divide our forces and send key personnel to interact with industry leaders at each gathering — to bring you the news and developing stories you need to keep on the forefront of change.
If you’re at ION GNSS+ or Intergeo, look for these faces, come up and introduce yourselves. We want to talk with you! If you’re not fortunate enough to attend either conference, look to our website, newsletters and this magazine for product launches, videos and in-depth stories filed from the developing frontiers of PNT. We’ll be reporting !!Live!! and for weeks, even months, to come.
Attending Intergeo in Berlin:
Burch
Barwacz
Joyce
Gerard
Tim Burch is our survey editor; in his day job he’s a professional surveyor and board of directors secretary of that profession’s national society.
Allison Barwacz is digital media content producer for North Coast Media (NCM, that’s us) with a passion for videography and writing.
Mike Joyce and Ryan Gerard, senior account manager and account manager, respectively, work closely with our marketing partners, who make this magazine and multi-media communications channel possible.
Attending ION GNSS+ in Portland:
Stoltman
Whitford
Mitchell
Cozzens
Harms
Sabau
Limpert
Cameron
Langley
Kevin Stoltman is founder and president of NCM, with a distinguished career in business-to-business publishing.
Marty Whitford is editorial director and publisher; earlier, he actually worked at GPS World and attended ION-GNSS 2004.
Michelle Mitchell is account manager for GPS World and senior marketing and event manager for NCM. She knows the GPS industry landscape and players extremely well.
Tracy Cozzens is our managing editor, with her hands on all the controls.
Joelle Harms is an award-winning digital media manager, focused on content planning and creation.
Joe Sabau is an account manager with a keen eye for market trends.
Kelly Limpert is a digital media content producer developing a strong online and social media presence for all of our partners.
Richard Langley is GPS World’s innovation editor and a professor at the University of New Brunswick.
Even a GNSS receiver that can supply raw pseudorange and carrier-phase measurements now costs only a few hundred dollars, and in this month’s column, a couple of researchers from Down Under pit a couple of these receivers up against a couple of survey-grade receivers. Did this cheap receiver turn out to be a good thing?
By Robert Odolinski and Peter J.G. Teunissen
ALL GOOD THINGS ARE CHEAP; ALL BAD ARE VERY DEAR. That’s what the famous American essayist (and surveyor) Henry David Thoreau wrote in his diary on March 3, 1841. He was likely referring, in part, to the cheapness of the things he came across in nature such as birdsong or the plants and trees on the shores of Walden Pond and the dearness of some luxuries and comforts of civilization, which he tended to eschew. But what has that got to do with GPS, you might ask?
When they were first introduced in the late 1970s and early 1980s, GPS receivers were very dear. Many of them sold for anywhere from $50,000 to $250,000, which would be equivalent to about twice those amounts in today’s dollars. The first civilian receivers were large bulky affairs. As I documented in this column in April 1990 (“Smaller and Smaller: The Evolution of the GPS Receiver”), the “first commercially available GPS receiver was the STI-5010 built by Stanford Telecommunications Inc. It was a dual-frequency, C/A- and P-code, slow-sequencing receiver. Cycling through four satellites took about five minutes, and the receiver unit alone required about 30 centimeters of rack space. External counters, also requiring rack space, made pseudorange measurements. An external computer controlled the receiver and computed positions.” While it could be transported in a small truck (and some were), it was not designed for portability and ease of use by surveyors or geodesists.
Then, in 1982, Texas Instruments introduced the first relatively compact civil GPS receiver, the TI 4100, also known as the Navstar Navigator. And as I also noted in that column more than 15 years ago, this “receiver could make both C/A- and P-code measurements along with carrier-phase measurements on both L1 and L2 frequencies. Its single hardware channel could track four satellites simultaneously through a multiplexing arrangement. The 37 × 45 × 21-centimeter receiver/processor had a handheld control and display unit and an optional dual-cassette data recorder for saving measurements for post-processing. The unit, although portable, weighed 25 kilograms and consumed 110 watts of power (the receiver doubled as a hand warmer). Field operation required a supply of automobile batteries.”
My, how things have changed. Beginning around 1990, receivers steadily got smaller and smaller and cheaper and cheaper. Survey-grade GNSS (not just GPS) receivers can now be purchased for well under $10,000 and consumer-grade units sell for as little as a hundred dollars or less. And, of course, the GNSS modules inside smartphones and other devices cost manufacturers only a couple of dollars or so.
But even a GNSS receiver that can supply raw pseudorange and carrier-phase measurements now costs only a few hundred dollars, and in this month’s column, a couple of researchers from Down Under pit a couple of these receivers up against a couple of survey-grade receivers. Did this cheap receiver turn out to be a good thing?
Read on to find out.
GPS has been the number-one positioning tool for a range of applications during the past few decades. The integration of the emerging global navigation satellite systems, such as the Chinese BeiDou Navigation Satellite System (BDS), can give improved precise (millimeter- to centimeter-level) real-time kinematic (RTK) positioning. When BDS is combined with GPS, about double the number of satellites are visible in the Asia-Pacific region, which can make single-frequency RTK and low-cost receiver RTK positioning possible.
In this article, we will analyze the performance of L1 GPS + B1 BDS in Dunedin, New Zealand, using low-cost receivers. We compare their performance to that of L1+L2 GPS survey-grade receivers.
First, we describe the GPS+BDS functional and stochastic models and the data used for our evaluations. Least-squares variance component estimation (LS-VCE) is used as a means to determine the code and phase (co)variances to formulate a realistic stochastic model. (An incorrect stochastic model will deteriorate the ambiguity resolution and consequently the achievable positioning precisions.)
Having correctly defined the stochastic model, we focus on the positioning performance. We investigated the ambiguity resolution and positioning performance, both formally and empirically, for customary and high-elevation cut-off angles. The high cut-off angles are used to mimic situations when low-elevation multipath is to be avoided. Lastly, we compared all our results between using low-cost and survey-grade antennas.
GPS+BDS POSITIONING MODEL
The model that we used for positioning is given as follows. Assume that sG + 1 GPS satellites are tracked on fG frequencies and sB + 1 BDS satellites on fB frequencies. As we apply system-specific double-differencing (DD), one pivot satellite is used per system. The total number of DD phase and code observations per epoch then equals 2 fGsG + 2 fBsB. We assume for now that cross-correlation between frequencies as well as code and phase is absent. The combined multi-frequency short-baseline GPS+BDS model is then defined as follows.
The system-specific DD phase and code observation vectors are denoted as φ* and p*, respectively, with * = {G, B} where G = GPS and B = BDS. The single-epoch GNSS model of the combined system is given as
(1)
and
(2)
in which
is the combined phase vector,
is the combined code vector,
is the combined integer ambiguity vector,
is the real-valued baseline vector,
is the combined phase random observation noise vector,
is the combined code random observation noise vector, and
D[.] denotes the dispersion operator.
The entries of the baseline design and wavelength matrices are given as
where is the x 1 vector of 1s, is the differencing matrix, is the unit matrix, the geometry-matrices GG and GB contain the undifferenced receiver-satellite unit direction vectors for GPS and BDS, respectively, is the wavelength of frequency , denotes the Kronecker product, and “diag” and “blkdiag” indicate diagonal and block diagonal matrices, respectively. The entries of the positive definite variance matrices are given as
(3)
where , denote the phase and code standard deviation, respectively, and the satellite elevation-angle-dependent weight.
The model in Equation 1 applies to short baselines, and thus the ionospheric and tropospheric delays are assumed absent. The broadcast ephemerides are used to obtain the satellite coordinates. Further, the Least-squares AMBiguity Decorrelation Adjustment (LAMBDA) technique is used to estimate the integer ambiguities a. The observation noise vectors εand e, respectively, are zero-mean vectors, provided that no multipath is present in Equation 1.
EXPERIMENT SETUP
The GNSS receivers we used are depicted in FIGURE 1. Firstly, two low-cost single-frequency receivers were set up to collect L1+B1 GPS+BDS data for two days. These receivers cost a few hundred U.S. dollars. Since the patch antennas we used have been shown to have less effective signal reception and multipath suppression in comparison to survey-grade antennas, the receivers that collected data for two days were additionally connected to such antennas. These antennas have a cost of slightly more than US$1,000 per antenna. To compare the low-cost solution to a survey-grade receiver-solution, two such receivers (which cost several thousand U.S. dollars) were connected to the same survey-grade antennas through splitters and collected L1+L2 GPS data. A detection, identification and adaption procedure was used to eliminate any outliers.
FIGURE 1. Low-cost single-frequency receivers collecting GPS+BDS data for single-baseline RTK, with patch antennas (left) and survey-grade antennas (right) on Jan. 4–6 and Jan. 6–8, 2016, respectively. Survey-grade dual- frequency GPS receivers were connected to the same survey-grade antennas simultaneously to truly track the same GPS constellation.
FIGURE 2 depicts the corresponding redundancy of the two receiver models (that is, the number of observations minus the number of estimated unknowns) together with the number of satellites over 48 hours (30-second epoch interval). The number of BDS satellites (magenta lines) is overall smaller than when compared to GPS (blue lines) in Dunedin. However, Figure 2 also shows that the model strength of L1+B1 GPS+BDS, as measured by its redundancy, is almost similar to that of L1+L2 GPS except for some hours at the middle of the two days. This implies that the two receiver models can potentially give competitive RTK ambiguity resolution and positioning performance. This is however only true if the receiver code and phase observation noise would be of similar magnitude between the receivers used, hence the need for an analysis of the receiver observation precision.
FIGURE 2. Redundancy (left) and number of satellites (right) of L1+B1 GPS+BDS and L1+L2 GPS during Jan. 6–8, 2016, (48 hours) for an elevation cut-off angle of 10°.
In our receiver evaluations, we determined a set of reference ambiguities by using a known baseline and treating them as time-constant parameters over the two days in a dynamic model.
LOW-COST RTK POSITIONING
The code and phase variances were estimated by LS-VCE using data independent from the data used for the following positioning analysis. The variances are needed to formulate a realistic stochastic model, whereas an incorrect stochastic model will deteriorate the ambiguity resolution and consequently the achievable positioning precisions. TABLE 1 depicts the corresponding estimated standard deviations (STDs) used for our positioning models.
TAB LE 1. Zenith-referenced undifferenced code and phase standard deviations estimated by least-squares variance component estimation.
Table 1 shows that the code precision of L1 GPS and B1 BDS improves significantly when the survey-grade antennas are used instead of patch antennas (49 centimeters STD for L1/B1 that decreases to about 30 centimeters), due to their better signal reception and multipath suppression abilities. For testing our stochastic model, we used data that is independent from the data used to estimate the code/phase precision.
Positioning Performance. The single-epoch (instantaneous) RTK positioning results for 24 hours data are shown in FIGURE 3, with ambiguity-float solutions shown at the top and ambiguity-fixed solutions at the bottom. Only the correctly fixed solutions are depicted as determined by comparing the instantaneously estimated ambiguities to the set of reference ambiguities. The 95% empirical and formal confidence ellipses and intervals are shown in green and red, respectively. They were computed from the empirical and formal position variance matrices. The empirical variance matrix was estimated from the positioning errors as obtained from comparing the estimated positions to precise benchmark coordinates. The formal variance matrix used was determined from the mean of all single-epoch formal variance matrices.
FIGURE 3. Horizontal (north (N), east (E)) position scatter and corresponding vertical (U) time series of the float (top) and correctly fixed (bottom) L1+B1 GPS+BDS single-epoch RTK solutions for an elevation cut-off angle of 10°. The 95% empirical and formal confidence ellipses and intervals are shown in green and red, respectively. The 24 hour (30 second) period is 22:00-22:00 UTC Jan. 5-6, 2016, for patch antennas in (a) and 21:48-21:48 UTC Jan. 8-9, 2016, for survey-grade antennas in (b), which are periods independent of the periods used to determine the stochastic model through the code/phase STDs in Table 1.
Figure 3 shows a good fit between the formal and empirical confidence ellipses/intervals, which thus illustrates realistic LS-VCE STDs in Table 1 that were used in the stochastic model. Note also the two-order of magnitude improvement when going from float to fixed solutions, and that the low-cost receiver plus survey-grade antenna has the most precise ambiguity-float positioning solutions.
Ambiguity Resolution and Positioning Performance for Higher Cut-Off Angles. We subsequently investigated the low-cost L1+B1 GPS+BDS performance for high elevation cut-off angles, so as to mimic situations in urban canyon environments or when low-elevation-angle multipath is present and is to be avoided. We have made comparisons to the survey-grade L1+L2 GPS results. It has been shown that a good ambiguity resolution performance does not necessarily imply a good positioning performance, so we investigated what effect this has on our positioning models.
The following integer least-squares (ILS) success rates (SRs) are thus computed based on epochs with the condition of positional dilution of precision (PDOP) ≤ 10 and averaged over all epochs over two days of data. By including and excluding epochs with large PDOPs, we can show how the positioning performance of the different models is affected by poor receiver-satellite geometries. To better understand how this exclusion of epochs with large PDOPs also influenced the empirical ambiguity-correctly-fixed positioning performance, we constructed TABLE 2, which shows the corresponding positioning STDs for two days of data. These STDs were computed by comparing the estimated positions to precise benchmark coordinates. In addition to the positioning performance, we depict in Table 2 the corresponding empirical ILS SR for full ambiguity-resolution, which is given by the ratio of the number of correctly fixed epochs to the total number of epochs.
TABLE 2. Single-epoch empirical STDs (N, E, U) of correctly fixed positions for the three positioning models together with their ILS SR for four elevation cut-off angles and 48 hours of data (Jan. 4–6 and Jan. 6–8, 2016). The empirical STDs and ILS SRs are also shown when conditioned on PDOP ≤ 10.
Table 2 shows that the L1+B1 low-cost receiver plus patch antenna combination has (as expected) smaller SRs in comparison to those when the survey-grade antenna is used. This latter combination has comparable SRs to the (PDOP-conditioned) SRs of the survey-grade L1+L2 GPS receiver for cut-off angles up to 25°.
In support of better understanding Table 2, FIGURE 4 shows typical positioning results for the different receiver and antenna combinations with elevation cut-off angles of 10° (top two rows) and 25° (bottom two rows). The first and third rows show the local horizontal (N, E) positioning scatterplots and the second and fourth rows the vertical (U) time series over two days of data. The float solutions are depicted in gray, and incorrectly and correctly fixed solutions in red and green, respectively. The zoom-in is given to better show the spread of the correctly fixed solutions with millimeter-centimeter level precisions. The formal ambiguity-float STDs are also shown under the up time series to reflect consistency between the empirical and formal positioning results.
FIGURE 4. Horizontal (N, E) scatterplots and vertical (U) time series for L1+B1 low-cost receiver with patch antenna (first column) with 99.5% (89.8%) ILS SR, L1+B1 low-cost receiver with survey-grade antenna (second column) with 100% (97.8%) ILS SR, and survey-grade L1+L2 GPS (third column) with 100% (94.1%) ILS SR, using 10° (top two rows) and 25° (bottom two rows) cut-off angles respectively (Jan. 4–6, 2016, for low-cost receiver with patch antenna and Jan. 7–8, 2016, for the low-cost and survey-grade receivers with survey-grade antennas). The SRs are conditioned on PDOP ≤ 10 and computed based on all epochs. Below the vertical time series, the ADOP is depicted in blue color, the 0.12-cycles level as red, and ambiguity-float vertical formal STDs are shown in gray.
We also depict in Figure 4 the ambiguity dilution of precision (ADOP) as an easy-to-compute scalar diagnostic to measure the intrinsic model strength for successful ambiguity resolution. The ADOP is defined as
(cycles) (4)
with n being the dimension of the ambiguity vector, the ambiguity variance matrix, and |.| denoting the determinant. ADOP gives a good approximation to the average precision of the ambiguities, and it also provides for a good approximation to the ILS SR. The rule-of-thumb is that an ADOP smaller than about 0.12 cycles corresponds to an ambiguity SR larger than 99.9%.
Figure 4 shows that more solutions are incorrectly fixed (red dots) when the ADOPs (blue lines) are larger than the 0.12 cycle level (red dashed lines). The figure also reveals that the L1+B1 low-cost receiver plus patch antenna combination achieves an ILS SR (99.5%) similar to that of the survey-grade L1+L2 GPS receiver (SR of 100%) for the cut-off angle of 10°. This ILS SR corresponds to the availability of correctly fixed solutions (green dots) with millimeter-centimeter level positioning precision over the two days. The L1+L2 GPS receiver has, moreover, large ambiguity-fixed positioning excursions at the same time as the formal STDs are large for the cut-off angle of 25° due the poor GPS-only receiver-satellite geometry for this high cut-off angle. This is also reflected by the corresponding relatively large ambiguity-fixed STDs depicted in Table 2 that are improved from decimeter- to millimeter-level when the PDOP ≤ 10 condition is applied. Figure 4 also shows that the L1+B1 low-cost receiver with the survey-grade antenna has a larger SR of 97.8% when compared to the PDOP-conditioned SR for L1+L2 GPS of 94.1% for the cut-off angle of 25° (see also Table 2), owing to the use of BDS that significantly improves the receiver-satellite geometry.
Finally, we also tested the low-cost receiver-solution (with survey-grade antennas) for a baseline length of 7 kilometers, where (small) residual slant ionospheric delays are present. It was shown that this combination still has the potential to achieve ambiguity resolution and positioning performance competitive with the survey-grade receiver-solution.
CONCLUSIONS
In this article, we evaluated a low-cost L1+B1 GPS+BDS RTK setup and compared its ambiguity resolution and positioning performance to a survey-grade L1+L2 GPS solution in Dunedin, New Zealand. The LS-VCE procedure was used to determine the variances of the low-cost receivers. The estimated variances are needed so as to formulate a realistic stochastic model, otherwise the ambiguity resolution and hence the achievable positioning precisions would deteriorate.
Since we analyzed a short baseline, the LS-VCE variances were shown to likely be affected by multipath. To mitigate multipath we connected the low-cost receivers to survey-grade antennas with better signal reception and multipath suppression abilities. It was shown that the survey-grade antennas can significantly improve the performance for the low-cost receivers so that the code/phase noise estimates more resemble that of survey-grade receivers. The LS-VCE STDs were furthermore shown to be realistically estimated for an independent time period.
We also demonstrated that the low-cost receivers can give competitive instantaneous ambiguity resolution and positioning performance to that of the survey-grade receivers. This is particularly true when the low-cost receivers are connected to survey-grade antennas.
ACKNOWLEDGMENTS
This article is based on the paper “On the Performance of a Low-cost Single-frequency GPS+BDS RTK Positioning Model” presented at the 2017 International Technical Meeting of The Institute of Navigation held Jan. 30-Feb. 1, 2017, in Monterey, California.
Ryan Cambridge at the School of Surveying, University of Otago, collected the low-cost receiver data. Author Peter J.G. Teunissen was supported by an Australian Research Council Federation Fellowship. All of this support is gratefully acknowledged.
MANUFACTURERS
The low-cost receivers used in the research were u-blox EVK-M8T receivers. The survey-grade receivers were Trimble NetRS receivers. The patch antennas were u-blox ANN-MS antennas, while the survey-grade antennas were Trimble Zephyr 2 GNSS antennas.
ROBERT ODOLINSKI conducted his Ph.D. studies at Curtin University, Perth, Australia, from 2011 to 2014. His research focus is next-generation multi-GNSS integer ambiguity resolution enabled precise positioning. In 2015, Odolinski started his position as a lecturer/research fellow in geodesy/GNSS at the School of Surveying, University of Otago, New Zealand.
PETER J.G. TEUNISSEN is a professor of geodesy and navigation and the head of the Curtin GNSS Research Centre, Curtin University. He is also with the Department of Geoscience and Remote Sensing, Delft University of Technology, Delft, The Netherlands. His research interests include multiple GNSS and the modeling of next-generation GNSS for high-precision positioning, navigation and timing applications.
FURTHER READING
• Authors’ Conference Paper
“On the Performance of a Low-cost Single-frequency GPS+BDS RTK Positioning Model” by R. Odolinski and P.J.G. Teunissen in Proceedings of the 2017 International Technical Meeting of The Institute of Navigation, Monterey, California, Jan. 30 – 1 Feb., 2017, pp. 745–753.
• Authors’ Related Work
“Single-Frequency, Dual-GNSS Versus Dual-frequency, Single-GNSS: A Low-cost and High-grade Receivers GPS-BDS RTK Analysis” by R. Odolinski and P.J.G. Teunissen in Journal of Geodesy, Vol. 90, No. 11, 2016, pp. 1255–1278, doi:10.1007/s00190-016-0921-x.
“Combined BDS, Galileo, QZSS and GPS Single-frequency RTK” by R. Odolinski, P.J.G. Teunissen and D. Odijk in GPS Solutions, Vol. 19, No. 1, 2015, pp. 151–163, doi:10.1007/s10291-014-0376-6.
“Instantaneous BeiDou+GPS RTK Positioning With High Cut-off Elevation Angles” by P.J.G. Teunissen, R. Odolinski and D. Odijk in Journal of Geodesy, Vol. 88, No. 4, 2014, pp. 335–350, doi: 10.1007/s00190-013-0686-4.
“The Future of Single-Frequency Integer Ambiguity Resolution” by S. Verhagen, P.J.G. Teunissen and D. Odijk in Proceedings of the VII Hotine-Marussi Symposium on Mathematical Geodesy, Rome, June 6–10, 2009, edited by N. Sneeuw, P. Novák, M. Crespi and F. Sanso, International Association of Geodesy Symposia, Vol. 137, 2012, pp. 33–38, doi:10.1007/978-3-642-22078-4 5.
“Centimeter-Level Positioning for UAVs and Other Mass-Market Applications” by C. Mongredien, J.-P. Doyen, M. Strom and D. Ammann in Proceedings of ION GNSS+ 2016, the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation, Portland, Oregon, Sept. 12–16, 2016, pp. 1441–1454.
“Initial Assessment of the COMPASS/BeiDou-2 Regional Navigation Satellite System” by O. Montenbruck, A. Hauschild, P. Steigenberger, U. Hugentobler, P.J.G. Teunissen and S. Nakamura in GPS Solutions, Vol. 17, No. 2, 2013, pp. 211–222, doi:10.1007/s10291-012-0272-x.
• LAMBDA
“On the Reliability of Integer Ambiguity Resolution” by S. Verhagen in Navigation, Vol. 52, No. 2, Summer 2005, pp. 99–110, doi: 10.1002/j.2161-4296.2005.tb01736.x.
“ADOP in Closed Form for a Hierarchy of Multi-frequency Single-baseline GNSS Models” by D. Odijk and P.J.G. Teunissen in Journal of Geodesy, Vol. 82, 2008, pp. 473–492, doi: 10.1007/s00190-007-0197-2.
By Omar Garcia Crespillo, Daniel Medina, Anja Grosch, Jan Skaloud and Michael Meurer / Presented at the European Navigation Conference, Lausanne, Switzerland, May 2017
Simulation Comparison: Classical GNSS/INS EKF and robust Huber EKF. Click to enlarge.
We designed a tightly-coupled integration between GNSS and inertial navigation systems (INS) where we modify the update step of a classical Extended Kalman Filter (EKF) to consider different robust estimators (such as M-estimators). We consider different faulty scenarios where the pseudoranges contain one or several non-modeled biases. The tightly-coupled GNSS/INS robust Kalman filter performance in the presence of biases is compared with the classical EKF and with a loosely-coupled Robust-GNSS/INS approach. The robust tightly-coupled version is able to minimize more efficiently the biases effect thanks to the direct redundancy of the inertial sensor within the robust estimator.
We set a simulated scenario based on a realistic trajectory and generate both GNSS and inertial measurements following state-of-the-art error models. We analyze the filter behavior under the presence of pseudorange measurement faults. For that purpose, we have run 100 Monte Carlo simulations over the given trajectory, and we have generated synthetic pseudorange biases of 40 meters in satellites PRN 18 and PRN 24 every 20 seconds. The filter error performance in the position domain is shown for the classical EKF and for a robust EKF based on Huber estimation criteria, the mean simulation error as well as the 95 error confidence interval. The classical EKF is highly affected by the sudden biases, and their effect influences for some seconds the estimation, while the robust Huber EKF is less sensitive to the presence of these biases because it is able to better adjust the estimation to minimize their effect in the final position estimation error.
Figure 1. Galileo constellation and occupation status of orbital slots (RAAN: right ascension of the ascending node, May 9, 2017). (Source: ESA)
What to Expect with the Current Constellation
This article demonstrates the benefits of Galileo integration for high-precision real-time kinematic (RTK) through representative case studies, considering baseline length, multipath impact and tree canopy.
The results confirm usability of the current Galileo constellation in high-precision RTK applications and show improved availability, accuracy, reliability and time-to-fix in difficult measuring environments.
Plus, Galileo-only RTK positions are compared with GPS-only and GLONASS-only solutions.
By Xiaoguang Luo, Jun Chen and Bernhard Richter, Leica Geosystems AG
Until now, based on simulated and observed data, the benefits of Galileo (FIGURE 1) for high-precision RTK have been investigated in single-base RTK and network RTK solutions. Building on the results of previous studies that frequently employed theoretic analysis and simulation, we present the benefits of Galileo for high-precision RTK based on real observations from the current Initial Operational Capability (IOC) satellite constellation. Using up-to-date real-time corrections including Galileo, we analyze the performance of network RTK under different measuring conditions with respect to availability, accuracy, reliability and time-to-fix.
To achieve the maximum inter-operability with other GNSS con-stellations, all the Galileo signals in the E1 and E5 band, i.e. E1, E5a, E5b and AltBOC (alternative binary offset carrier), are used for positioning in the latest proprietary firmware and receivers (see “Manufacturers” section for details).
The Galileo E1 signal is overlapped with the GPS L1 signal at a center frequency of 1575.420 MHz, whereas the Galileo E5a and GPS L5 signals are overlapped at 1176.450 MHz. As far as BeiDou is concerned, the E5b frequency of Galileo corresponds to the B2 frequency of BeiDou-2 at 1207.140 MHz.
The AltBOC signal is also supported in order to benefit from its superior performance in multipath suppression. The availability of more than two frequencies is beneficial for ionospheric modeling, which plays an important role in ambiguity resolution on the fly.
In addition, multi-frequency RTK provides more immunity to temporary interruption of GNSS signals caused by interference or by site-specific effects like multipath. When forming linear combinations, the incorporation of multi-frequency signals enhances flexibility and robustness, where the mathematical correlations introduced by including the same signal in different linear combinations of the same type need to be handled properly in RTK algorithms.
By enabling the tracking of Galileo satellites in the aforementioned firmware, the Galileo signals will be used in different RTK position types by default, including navigation position, phase-aided differential code position, extended RTK (xRTK) position and RTK fixed position. When compared to a standard RTK fix, an xRTK fix is provided at a slightly lower accuracy level, but with higher availability in difficult environments such as urban canyons and dense canopy.
In terms of RTK correction data formats, Galileo is included in the standardized RTCM v3 MSM format and in the proprietary 4G format. To use Galileo in network RTK, the real-time products provided by network correction services need to include Galileo as well. In the latest version of a proprietary GNSS network software, Galileo is used in network processing to provide RTK corrections via the individualized master-auxiliary (iMAX) method and the virtual reference station (VRS) method in the RTCM 3.2 MSM formats.
RTK PERFORMANCE CHARACTERISTICS
Multi-constellation and multi-frequency GNSS RTK is a complex real-time process, aiming to provide cm-level positioning accuracy with as few as possible data epochs for variable user kinematics and even in difficult measuring environments. Therefore, RTK performance characteristics need to be carefully selected to be able to evaluate the system as a whole and to address users’ concerns in their applications.
The following parameters are used in this article to assess the benefits of Galileo for high-precision RTK:
Satellite usage. Number of satellites used in RTK fixed solutions with an elevation cut-off angle of 10°;
Availability. Percentage of RTK fixed positions relative to all positions obtained during a time period;
Accuracy. Deviation of RTK fixed positions from ground truth with a higher degree of accuracy, where the ground truth can be determined by means of a total station or by post-processing long-term GNSS data;
Reliability. Percentage that the position error (with respect to ground truth) is less than 3 x coordinate quality (CQ) indicator;
Time to Fix. Time needed to regain an RTK fixed solution after losing ambiguity fix provided that GNSS signal tracking is not interrupted.
OPEN-SKY CASE STUDY
The open-sky case study was performed in the Heerbrugg testbed. Two receivers were connected to a single antenna via a four-way antenna splitter. One receiver received four-system iMAX corrections in the RTCM v3 MSM format over a short baseline of 2 km, whereas the other received RTK data of the same type over a long baseline of 116 km. By considering different baseline lengths, the open-sky experiment focused on the usability of the current Galileo constellation in GNSS RTK under normal conditions. Two days of 1-Hz GNSS data were investigated with respect to satellite usage and positioning accuracy.
Using different combinations of GNSS to analyze the short baseline data — GPS+GLO (GG), GPS+GLO+BDS (GGB) and GPS+GLO+GAL+BDS (GGGB) — the mean numbers of used satellites are 15, 17 and 20, respectively, where the elevation cut-off angle was set to 10°. On average, three Galileo satellites contribute to RTK fixed solutions.
For the four-system combination GGGB, Figure 2 shows the satellite usage for each individual system over the two-day period. It can be seen that for a short baseline of 2 km, a maximum number of four Galileo satellites can be used for positioning. In fact, during 80.3% of the whole test period, the number of Galileo satellites used in RTK fixed solutions is equal to or greater than the number of BeiDou satellites used.
Figure 2. Number of satellites used in RTK fixed positions with GGGB under open sky (iMAX, RTCM v3 MSM, baseline length: 2 km, GGGB: GPS+GLO+GAL+BDS, DOY: day of year).
Table 1 provides statistics on Galileo satellite usage in case of GGGB for different baseline lengths. As would be expected, the number of Galileo satellites used decreases with an increasing baseline length. In approximately 41% of the cases, three Galileo satellites are used in the short baseline test, whereas two Galileo satellites are used in the long baseline test.
Moreover, the probability that no Galileo satellites are involved in a four-system combined solution grows significantly from 1.9% to 15.0% as the baseline length increases from 2 km to 116 km. The probability that only one Galileo satellite is used under open sky is relatively small, amounting to around 0.5%. This is reasonable since no benefits for high-precision RTK are expected in this particular situation. Regarding the short baseline case, there is a 97.7% probability that at least two Galileo satellites are used for positioning, whereas this probability decreases to 84.4% in the long baseline case.
Table 1. Probability [%] that n Galileo satellites are used in RTK fixed positions with GGGB during the two-day period of the open-sky experiment (iMAX, RTCM v3 MSM, GGGB: GPS+GLO+GAL+BDS).In terms of positioning accuracy, Figure 3 compares the 3D errors from analyzing the long baseline data with different GNSS constellations. Regarding the entire two-day period illustrated in Figure 3a, the integration of BeiDou (GG vs. GGB) and Galileo (GGB vs. GGGB) results in higher position repeatability with more consistent errors. For a selected period of 12 hours, Figure 3b highlights the advantages of Galileo in reducing large 3D errors from 6–8 cm to 3–4 cm, where two or three Galileo satellites are used in case of GGGB.
Figure 3. 3D errors of RTK fixed positions under open sky (iMAX, RTCM v3 MSM, baseline length: 116 km, GG: GPS+GLO in green, GGB: GPS+GLO+BDS in blue, GGGB: GPS+GLO+GAL+BDS in red, DOY: day of year) (a) Entire two-day period, (b) Selected 12-hour period (28–40 h).
MULTIPATH CASE STUDY
In this case study, a GNSS smart antenna was set up in a location with strong multipath effects, where GNSS signals were obstructed and reflected by the surrounding buildings (Figure 4). This test setup simulates the use case that a user measures a point near a building with degraded GNSS signal reception, even at high elevation angels.
Figure 4. Test setup in a strong multipath environment in Heerbrugg (rover: GS16, antenna height: 1.8 m) (a) View from the south, (b) View from the north.
The default elevation cut-off angle of 10° was applied. The receiver received four-system VRS corrections in the RTCM v3 MSM format, where the distance to the physical reference station was approximately 200 m. Three hours of 1-Hz GNSS data were analyzed with respect to accuracy, reliability and time to fix.
Figure 5 illustrates the 3D errors from multi-GNSS RTK with and without Galileo (GGGB vs. GGB), along with the number of used satellites. Regarding the periods marked with dashed rectangles, the inclusion of two or three Galileo satellites (Figure 5b) leads to significant improvements in positioning accuracy at the few cm to dm level (Figure 5a). By comparing the empirical cumulative distribution function (CDF) of the 3D errors, the probability that 3D error is within 5 cm increases from 70% to 85% if Galileo is used, even with a maximum number of three satellites.
Figure 5. Impact of Galileo integration on RTK positioning accuracy under strong multipath (VRS, RTCM v3 MSM, GGB: GPS+GLO+BDS in blue, GGGB: GPS+GLO+GAL+BDS in red, DOY: day of year) (a) 3D errors of RTK fixed positions, (b) Number of used satellites (Galileo in green).
Tables 2 and 3 provide the root mean square (RMS) errors and reliability of RTK fixed positions from the multipath experiment, respectively. By using Galileo in high-precision RTK, the 3D RMS error is significantly reduced by 56.3% in this case study, from 0.080 m (GGB) to 0.035 m (GGGB). When compared to the horizontal components, the height RMS error shows a larger relative improvement of 58.7% due to Galileo integration. The reliability reflects the consistency between the actual position error with respect to ground truth and the CQ indicator estimated based on mathematical models in RTK algorithms. As shown in Table 3, the 3D reliability improves by 7.3%, from 88.2% (GGB) to 95.5% (GGGB), where the increases for the horizontal components and height are comparable.
Table 2. Root mean square errors [m] of RTK fixed positions under strong multipath (VRS, RTCM v3 MSM, GGB: GPS+GLO+BDS, GGGB: GPS+GLO+GAL+BDS).Table 3. Reliability [%] of RTK fixed positions under strong multipath (VRS, RTCM v3 MSM, GGB: GPS+GLO+BDS, GGGB: GPS+GLO+GAL+BDS).The time to fix (TTF) was determined by constantly re-initializing RTK once an ambiguity fix was gained. During the whole period of repeatedly resetting the RTK filter, the GNSS signals were tracked continuously without interruption. A total of 765 TTF values were obtained with GGB, whereas 1,128 TTF estimates were available with GGGB. The significantly larger number of the TTF samples from GGGB indicates higher availability of RTK fix if Galileo is used.
Figure 6 shows the statistical distribution of TTF with respect to Galileo integration. As can be seen in the empirical CDF in Figure 6a, it takes shorter time for GGGB to regain an ambiguity fix. As an example, GGGB allows ambiguity resolution within 5 s (10 s) with 46% (87%) probability, which is 29% (16%) higher than GGB. Regarding the boxplots of TTF in Figure 6b, GGGB shows a smaller median (by 25% from 8 s to 6 s) and a smaller interquartile range (IQR; by 50% from 4 s to 2 s) than GGB, where the IQR is the length of the box. This indicates that the integration of Galileo enables a faster ambiguity resolution with more consistent fixing performance.
Figure 6. Impact of Galileo integration on time to fix (TTF) statistics under strong multipath (VRS, RTCM v3 MSM) (a) Empirical cumulative distribution function (CDF) of TTF, (b) Boxplot of TTF with median and interquartile range (IQR).
CANOPY CASE STUDY
In this case study, a receiver was connected to an antenna under tree canopy (Figure 7), where GNSS signals are blocked, attenuated and reflected, leading to decreased number of observations, low data quality and degraded RTK performance.
Under these circumstances, the inclusion of Galileo satellites transmitting multi-frequency signals could be particularly beneficial for high-precision RTK. Using an elevation cut-off angle of 10°, the receiver received four-system iMAX corrections in the RTCM v3 MSM format, where the baseline length was 116 km. A long baseline was intentionally selected as an additional challenge for the RTK system. About seven hours of 1-Hz GNSS data were investigated regarding availability, accuracy and reliability.
Figure 7. Test setup under canopy in Heerbrugg (rover: GS10, antenna: AS10).
Figure 8 illustrates the impact of Galileo integration on RTK availability and accuracy under canopy, along with the number of used satellites. As can be seen in Figure 8a, the inclusion of Galileo improves the availability of RTK fixed positions by 12.2%, from 65.7% (GGB) to 77.9% (GGGB). Moreover, dm-level position errors are largely reduced, as shown in FigURE 8c. The improvements in availability and accuracy are achieved by using up to three Galileo satellites (Figure 8b). This demonstrates that the current Galileo constellation in the IOC phase brings considerable benefits to high-precision RTK under canopy conditions.
Figure 8. Impact of Galileo integration on RTK availability and accuracy under canopy (iMAX, RTCM v3 MSM, baseline length: 116 km, GGB: GPS+GLO+BDS in blue, GGGB: GPS+GLO+GAL+BDS in red, DOY: day of year) (a) Availability of RTK fixed positions over time, (b) Number of used satellites (Galileo in green), (c) 3D errors of RTK fixed positions.
Tables 4 and 5 provide the RMS errors and reliability of RTK fixed positions from the canopy experiment, respectively. The main factors degrading the RTK accuracy in this case study are not only the canopy environment, but also the long baseline length of 116 km. It can be seen in Table 4 that the integration of Galileo leads to a significant reduction of 3D RMS error by 23.7%, from 0.114 m (GGB) to 0.087 m (GGGB).
By comparing the 2D and 1D RMS errors, the benefits of Galileo for the height are more dominant than for the horizontal components, which was also observed in the multipath experiment (Table 2). In terms of reliability, only slight (below 2%) increases are visible in Table 5. 116km baseline length and heavy canopy are considered extreme conditions and beyond the standard conditions relevant for specifications. Considering reliability together with availability (Figure 8a), it is encouraging to see that both the RTK performance characteristics are improved in this case study.
Table 4. Root mean square errors [m] of RTK fixed positions under canopy (iMAX, RTCM v3 MSM, baseline length: 116 km, GGB: GPS+GLO+BDS, GGGB: GPS+GLO+GAL+BDS).Table 5. Reliability [%] of RTK fixed positions under canopy (iMAX, RTCM v3 MSM, baseline length: 116 km, GGB: GPS+GLO+BDS, GGGB: GPS+GLO+GAL+BDS).
GALILEO-ONLY RTK
To optimize the performance of multi-GNSS RTK positioning, the individual systems need to be fully understood and mastered. With a previous firmware release in August 2014, mass-market devices were able to perform GLONASS-only and BeiDou-only high-precision RTK. In 2014 tests, we compared the performance of GPS-only, GLONASS-only and BeiDou-only RTK at different accuracy levels. Considering that Galileo has reached the IOC phase, it is reasonable to assess the Galileo-only RTK performance with the latest firmware.
Due to the limited number of usable Galileo satellites, Galileo-only RTK positioning was carried out in the Heerbrugg open-sky testbed over a very short baseline of 1 m. In addition, the elevation cut-off angle was set to 0° in order to track as many Galileo satellites as possible simultaneously. Two receivers were connected to two choke-ring antennas with good low-elevation tracking ability. Single-base RTK positioning was performed with four-system corrections in the RTCM v3 MSM format. About one hour of 1-Hz GNSS data was analyzed with a special focus on positioning accuracy.
Figure 9 shows the 3D errors from GPS-only, GLONASS-only and Galileo-only RTK positioning, where the numbers of used satellites are 8–11, 7–9 and 5–6, respectively. During the test period, only three or four BeiDou satellites were tracked with poor geometry, making BeiDou-only RTK impossible. As the figure shows, the 3D errors from GPS-only and Galileo-only RTK are at a comparable level with similar RMS values, whereas the 3D RMS error from GLONASS-only RTK is almost twice as large as the GPS/Galileo-only case. Note that when compared to GPS-only RTK, almost half as many satellites are used in Galileo-only RTK.
Figure 9. 3D errors of RTK fixed positions from GPS-only, GLONASS-only and Galileo-only RTK under open sky (single-base RTK, baseline length: 1 m, RTCM v3 MSM, DOY: day of year, RMS: root mean square).
Figure 10 displays the statistical distribution of the 3D errors from GPS-only, GLONASS-only and Galileo-only RTK positioning. Regarding the empirical CDF in Figure 10a, GPS/Galileo-only RTK shows a clearly more favorable error distribution than the GLONASS-only case. Using only GPS or Galileo, the probability that 3D error is within 1 cm is above 80%, which is approximately 30% higher than using only GLONASS. For 3D errors ranging between 5 mm and 1.7 cm, Galileo-only RTK even provides a slightly higher cumulative probability than the GPS-only case. The 3D error boxplots in Figure 10b illustrate a similar pattern between GPS-only and Galileo-only RTK, which is superior to GLONASS-only RTK due to the significantly smaller median and IQR.
Figure 10. 3D error statistics from GPS-only, GLONASS-only and Galileo-only RTK under open sky (single-base RTK, baseline length: 1 m, RTCM v3 MSM). (a) Empirical cumulative distribution function (CDF) of 3D errors, (b) Boxplot of 3D errors (IQR: interquartile range).
CONCLUSIONS
With the declaration of Galileo Initial Services in December 2016, for the first time ever all GNSS users worldwide are able to use the positioning, navigation and timing information provided by Galileo’s global satellite constellation. Upon full system completion by 2020, Galileo will play an important role in high-precision GNSS applications for users around the world. This article showed representative case studies to understand the benefits of the current Galileo constellation for high-precision RTK. In addition to a multi-GNSS solution, the performance of Galileo-only RTK was presented. The main findings from the case studies can be summarized as follows:
In the open-sky test, with an elevation cut-off angle of 10°, on average three Galileo satellites can be used for high-precision multi-GNSS RTK. This leads to cm-level improvements in coordinate repeatability over a long baseline of 116 km.
In the multipath case study, the additional use of two or three Galileo satellites produces significant enhancements in positioning accuracy at the few cm to dm level, where the benefits for the height component are more significant. Moreover, the integration of Galileo increases the 3D reliability of RTK fixed positions by 7.3% and reduces the median time to fix by 2 s (25%).
In the canopy experiment, the inclusion of Galileo improves the availability of RTK fixed solutions by 12.2%. Furthermore, dm-level position errors are largely reduced.
When compared to GPS-only RTK, Galileo-only RTK provides a similar positioning accuracy over a 1-m baseline under open sky, where almost half as many satellites are used. The 3D RMS error from GLONASS-only RTK is approximately twice as large as the GPS/Galileo-only case.
The promising results achieved through Galileo integration already indicate the very important role of the European GNSS in high-precision, multi-frequency and multi-constellation RTK positioning. During the deployment of the Galileo system, more benefits can be expected in the near future.
ACKNOWLEDGMENTS
The staffs of Leica Geosystems AG (Heerbrugg/Switzerland), Christian Waese and Youssef Tawk, are gratefully acknowledged for support in setting up the variety of RTK network streams.
MANUFACTURERS
SmartWorx 6.16 of Leica Viva GNSS is the latest firmware cited and used in these high-precision RTK tests. Leica GNSS Spider 7.0.0 furnished the GNSS real-time corrections. The open-sky case study used two Leica Viva GS10 units connected to a Leica Viva AS10 antenna via a four-way antenna splitter. The multipath case study used a Leica Viva GS16 GNSS smart antenna. The canopy case study used a Leica Viva GS10 receiver and a Leica Viva AS10 antenna. The Galileo-only RTK test used two Leica Viva GS10 receivers and two Leica AR25 choke ring antennas.
Table 1. Capability and status of complementary positioning technologies. (Chart: GLA)
The General Lighthouse Authorities of the U.K. and Ireland (GLA) reached Initial Operational Capability for eLoran on the East coast of the U.K. Although it was shown to work well technically, it has not been possible to implement the system in Europe on a regional basis.
The GLA have also been involved in the potential development of other, non-satellite based, alternative systems. These may now form the basis of positioning resiliency either individually, or as a tapestry of systems serving the maritime navigator in Europe, unless current plans for commercial operation of eLoran come to fruition.
Here we consider the technical and regulatory status of eLoran in comparison with the other options, and explore necessary steps to protect the maritime navigator in the face of increasing GNSS outages. Several alternative backup technologies could be considered complementary to GNSS for future introduction into ships’ Integrated Navigation Systems. They have varying capabilities, and different limitations and levels of maturity, summarized in Table 1. Figure 1 shows estimated timescales for development and implementation.
Figure 1. Timeline for resilient PNT. (Image: GLA)
Conclusions
■ eLoran is the only complementary backup system that can be implemented within the timescale envisaged for the introduction of e-navigation; however, there are political obstacles to implementation, at least in Europe.
■ R-mode and possibly radar positioning could be introduced by about 2030; however, both have inherent coverage limitations. Feasibility studies are needed to assess their economic viability.
■ Other options, such as inertial systems and signals of opportunity, might emerge as viable alternatives by 2030, but there are large uncertainties about technical and regulatory matters.
■ Quantum devices and options such as bathymetric and geomagnetic positioning can only be considered as longer term and uncertain possibilities.
■ A multi-system solution may offer the best approach. The IMO concept of the Integrated Navigation System aboard vessels, incorporating a multi-system receiver, provides flexibility for the inclusion of the above positioning technologies, if and when they become available, at an affordable cost.
A: Integration with GNSS and other sensors in most every military vehicle or weapon-control system will enable inertial sensor developers to focus on driving improvements in performance for the two fundamental parameters that a sensor-fusion INS filter cannot estimate: noise and in-run bias stability. Ultra-tightly coupled sensor fusion of GNSS with range-, speed- and video position-sensing, with tactical and navigation grade inertial sensors optimized for noise and in-run, will enable design of robust GPS chip-level solutions for high-dynamic, high-performance navigation for nearly any military environment or engagement.
Michael Whitehead, chief technology officer, Hemisphere GNSS
A: Previously used for military applications, inertial technology has become mainstream as performance-to-cost has improved with the emergence of low-cost microelectromechanical systems (MEMS). Precise point positioning (PPP) advancements have driven GNSS accuracies to 4 cm or better, but long PPP initialization times are problematic in challenging environments where reconvergence is often required. Tightly coupled integration of PPP and navigation-quality MEMS will overcome limitations of both technologies, yielding high accuracy with high availability, even in challenging environments.
Chris Wheeler, manager, telematics and connected sites, Trimble Navigation
A: The availability of multi-frequency GNSS receivers with inertial components on a small lightweight board can now deliver centimeter-accurate INS/GNSS solutions, so that OEMs and integrators can significantly improve reliability and robustness in harsh or GNSS-denied applications or for solutions such as UAVs. The advances provided by MEMS inertial components increase overall efficiency by reducing the number of ground control points while still meeting the needs for a low weight and power consumption solution.
Harxon has introduced an advanced, high-speed, Bluetooth-enabled wireless rover radio.
The HX-DU1603D, designed for GNSS/RTK surveying and precise positioning, will be showcased this September at the Intergeo trade show in Berlin, Germany.
The HX-DU1603D is a lightweight, ruggedized UHF receiver designed for data communications between 410 MHz and 470 MHz in either 12.5 KHz or 25 KHz channels, which can be widely used in GNSS/RTK surveying and GNSS precise positioning fields.
It is equipped with a Bluetooth transceiver for wireless communications with external devices. It features a 6800 mAh rechargeable internal battery and configurable transmit power between 0.5W and 2W. Its IP67 waterproof capability allows long operating hours outdoors, the company said.
The HX-DU1603D rover radio is easy to operate and use. It is equipped with a 1.9-inch display screen that supports frequency, protocols, power display, serial port baud rate and air baud rate. By deploying these technologies, users can instantly communicate with GNSS precise positioning receivers with the same protocols throughout the world.
The rover radio HX-DU1603D has joint Harxon product lines, including 25W base radio HX-DU8602T with simplex and 35W base radio HX-DU8608D with duplex.
Here there be dragons. That phrase (or a variation of it) was used by early mapmakers to designate the unknown — and alert sailors to the danger of traveling into uncharted waters.
I’ve always admired explorers who dared to push the boundaries of the known world. We’ve moved from the Age of Exploration to the Age of Information, but exploration continues on frontiers big and small.
Today, of course, most people think of the world as having been mapped. They can simply call up Google maps on their smartphone and see not only the world, but their town, their street and their house — in representational cartography (traditional map), satellite imagery, or even street-view imagery.
Professionals in geographic information systems (GIS) know better. The world is still a mystery in uncounted areas. For one thing, it’s not static: Volcanoes form new land masses, storms change coastlines, the sea-level is rising. For another, there’s more to exploration than a basic map.
That’s where the GIS professional takes center stage, assessing an area beyond what is already known, using a variety of tools to collect and analyze data. As Esri defines it, a GIS lets us “visualize, question, analyze and interpret data to understand relationships, patterns and trends. GIS benefits organizations of all sizes and in almost every industry.” A software-based profession, GIS experts use GPS, GNSS and inertial to gather data, which is where this magazine comes in.
At GPS World, we share GIS developments in our Mapping Market Watch, Mapping Launchpad and at geospatial-solutions.com.
GPS signals are so weak, they cannot be used reliably where they are obstructed such as indoors or in concrete canyons. But if the satellites were much closer, their signals would be much stronger. The low Earth orbit Iridium constellation is already orbiting and providing a PNT service. This month we learn about its current capability and future promise.
By David Lawrence, H. Stewart Cobb, Greg Gutt, Michael O’Connor, Tyler G.R. Reid, Todd Walter and David Whelan
(A shortened version of “Innovation Insights” appeared in the magazine.)
INNOVATION INSIGHTS with Richard Langley
WHOA CANADA! July 1st marks Canada’s sesquicentennial. In 1867, four Canadian provinces, Ontario and Quebec (up to then known as the single Province of Canada), Nova Scotia and New Brunswick, joined together to form The Dominion of Canada — the name suggested by New Brunswick’s Sir Leonard Tilley. Other provinces came on board later with the last, Newfoundland and Labrador, joining in 1949.
Apart from my interest in educating all and sundry about the origins of the “true north, strong and free,” what has this got to do with GNSS or allied technologies? Well, it turns out that Canada has played and continues to play an important role in the development of communications and navigation technologies.
It started on Christmas Eve, 1906, when Canadian inventor Reginald Fessenden carried out the first amplitude modulation radio broadcast of voice and music. And in 1925, Edward “Ted” Rogers, a Canadian pioneer in the radio industry, invented a radio tube using alternating current that became a worldwide standard in radio circuits.
Many other developments in terrestrial communications took place in Canada over the years including microwave repeater technology and shortwave radio broadcasting from the famed transmitter plant (now defunct, unfortunately) established near Sackville, New Brunswick, during World War II.
There have also been significant Canadian advances in satellite technology. The first Canadian satellite, Alouette (French for “skylark”), was launched in September 1962 to study the ionosphere. Launched by the United States, it was the first satellite to be constructed by a country other than the U.S. or the Soviet Union. Several other Canadian ionospheric research satellites have been orbited since including CAScade, Smallsat and IOnospheric Polar Explorer or CASSIOPE, launched in September 2013. CASSIOPE carries eight instruments for studying the ionosphere including the University of New Brunswick’s GPS Attitude, Positioning, and Profiling instrument.
Canada has also been a leader in satellite communications technology. The first Anik geostationary satellite was launched in November 1972. (Anik means “little brother” in Inuktitut.) Eight more Anik satellites were launched subsequently including Anik F1R, which is also used to broadcast Wide Area Augmentation System information to GPS receivers. And the first satellite to explore the 14/12-GHz band for direct broadcasting to homes and businesses was Canada’s Communications Technology Satellite, dubbed Hermes, launched in January 1976.
And, of course, we don’t need to mention the Remote Manipulator System on the International Space Station, commonly known as Canadarm, nor the work of celebrity Canadian astronaut Col. Chris Hadfield.
In the area of satellite navigation, Canada is known for its development of techniques to use the U.S. Navy Navigation Satellite System or Transit for one-meter positioning accuracy permitting establishment of geodetic control points such as in Canada’s far north. Canada was also an early adopter of GPS and with software and hardware developments by industry, government and academia has made its mark in the world of precision positioning, navigation and timing.
Another Canadian initiative is the Aerion satellite-based air traffic surveillance system that will use the enhanced low Earth orbit Iridium constellation.
And we shouldn’t forget that Canada is slated to provide the search and rescue package for the GPS III satellites.
Speaking of GPS, we all know what a great technology it is, providing the “gold standard” in global satellite navigation. But it does have one dominant problem: the weakness of the signals. The signals are so weak that they cannot be used reliably where they are obstructed such as indoors or in concrete canyons. The problem stems from the fact that these medium Earth orbit satellites are far away and their energy is significantly spread out during their passage to Earth. If the satellites were much closer to the Earth, their signals would be much stronger. Mind you, you would need more satellites to provide global coverage. Fantasy? No. There is already a constellation of satellites in orbit providing such a PNT service. It is Iridium–the same constellation that will provide the Canadian-initiated aircraft tracking system–and in this month’s column we will learn about is current capability and future promise. Pretty neat, eh?
With the advent of smartphones, there are now more than four billion devices that make use of GNSS. These satellite navigation systems provide not just the blue dot representing location on our phones, but also support the critical infrastructure we rely upon.
The U.S. Department of Homeland Security recognizes that all 16 sectors of U.S. critical infrastructure depend on GPS — 13 of which have critical dependence. A recent report by London Economics estimates the cost of a GNSS outage to the U.K. alone would be over £1B per day.With autonomous systems on the rise, our reliance on GNSS will only be increasing.
As we become more dependent on this technology, we become vulnerable to its limitations. One major shortcoming is signal strength. Designed to work in an open-sky environment, GNSS is severely limited in deep attenuation environments, with little or no service in dense cities or indoors. Furthermore, we are susceptible to jamming where a 20-watt GNSS jammer can deny service over a city block.
The proximity of low Earth orbit (LEO) has the potential to provide much stronger signals than the distant GNSS core-constellations like GPS in medium Earth orbit (MEO). Today, the only LEO system with global coverage is the Iridium constellation used primarily for communications.
FIGURE 1 shows the 31-satellite GPS constellation in contrast with the 66-satellite Iridium network. The scale of the difference in distance (several Earth radii) is extraordinary. The result is that Iridium signals are 300 to 2,400 times stronger than GNSS signals on the ground, making them attractive for use in position, navigation and timing (PNT) applications where GNSS signals are obstructed.
FIGURE 1. The 66-satellite Iridium constellation in low Earth orbit and 31-satellite GPS constellation in medium Earth orbit.
LEO-based PNT is now mainstream, in the form of real-time signals that have been delivered over the Iridium satellite network since May 2016. This service is made possible by Satelles in partnership with Iridium Communications Inc. in a service called Satellite Time and Location (STL), a non-GNSS solution for assured time and location that is highly resilient and physically secure. Consumers, businesses and governments are already using these LEO-based signals in environments with high GNSS interference or occlusion.
The security features of these signals are also used to reliably validate GNSS PNT solutions in real time to help mitigate potential spoofing. Furthermore, the fast LEO orbits of Iridium generate Doppler-frequency-shift signatures significantly stronger than GPS, increasing the utility of the STL signal for positioning applications.
STL field tests demonstrate a positioning accuracy of 20 meters and timekeeping to within 1 microsecond, all in deep attenuation environments indoors. This adds substantial robustness in augmenting the GNSS core constellations like GPS and also allows for a standalone backup in many applications.
LEO Constellations: Past, Present, Future
In 1964, Transit (or the U.S. Navy Navigation Satellite System) became the first operational satellite navigation system. This constellation typically consisted of five to 10 satellites placed in polar orbits with an altitude of about 1,100 kilometers. Unlike many terrestrial radio navigation systems, a position fix was not instantaneous. It required 10 to 16 minutes of observation as a satellite passed overhead to achieve the needed geometric diversity. There was also latency; users had to wait for a satellite to come into view, which could take from 30 to 100 minutes.
The trade-off was accuracy; early performance was a few hundred meters and was later improved to 20 meters (and even down to about 1 meter for multiple-pass fixed-site surveys), the best performance of its day. In 1967, Transit became open for civilian use and remained operational until 1996 when GPS was at full operational capability.
The Soviet Union developed a system similar to Transit known as Parus/Tsikada, with first satellites on orbit in 1967. Parus/Tsikada operated on the same passive Doppler observation principle as Transit, on similar frequencies and in similar polar orbits.
Today, the largest satellite constellation with constant global coverage is Iridium. With 66 LEO satellites delivering worldwide satellite connectivity, including the poles, this system has tenfold more satellites than Transit had. Along with its strong signals compared to the GNSS core-constellations in MEO, Iridium’s global coverage makes it ideal for use in PNT applications where GNSS is obstructed.
Figure 1 shows the scale of the difference in altitude with Iridium at 780 kilometers and GPS at 20,200 kilometers. This has substantial implications not only for signal strength, but also for coverage.
Though Iridium has twice as many satellites as GPS, at the Equator users can often only see one satellite at a time, whereas they can see 10 from GPS. This was one of the fundamental trades considered in the design of the GPS constellation. The higher the altitude, the more each launch cost; the lower, the more satellites had to be built to provide coverage. To put this in perspective, global coverage for one satellite in view at all times requires fewer than 10 satellites in MEO, but requires closer to 100 in LEO.
Future LEO Constellations
The hundreds of LEO satellites needed to match the coverage of GPS may be coming. In late 2014 and early 2015, the International Telecommunication Union reported a half-dozen filings for spectrum allocation for large constellations of LEO satellites.
In January 2015, OneWeb announced a partnership with Virgin and Qualcomm to produce a constellation of 648 LEO satellites to deliver broadband Internet globally. This represents the next order of magnitude, with tenfold more satellites than Iridium.
Within days of this announcement, SpaceX, with support from Google, announced a similar ambition for a constellation of more than 4,000 LEO satellites.
In August 2015, Samsung expressed interest with a proposal for a LEO constellation of 4,600. Boeing joined the race in June 2016, announcing plans for a LEO constellation of nearly 3,000 satellites.
These LEO constellations are being proposed to keep up with the rising demand for broadband, not to replace ground infrastructure, and will provide Internet access to the 54% of the global population that lack that access.
TABLE 1 compares the GNSS core constellations in MEO to the big (Iridium), broadband (OneWeb, SpaceX, Boeing) and early navigation (Transit, Parus/Tsikada) LEO constellations.
TABLE 1. Constellation comparison.
LEO versus MEO
Low and medium Earth orbit each have their individual strengths and weaknesses in the context of navigation as summarized by TABLE 2.
TABLE 2. Comparison of LEO and MEO systems for navigation.
Closer to Earth, LEO offers less spreading loss and improved signal strength on the ground. FIGURE 2 shows that the signal spreading (or space) loss for Iridium is between –140 and –130 dB compared to GPS at –160 dB.
This stems from Iridium being 25 times closer to Earth than GPS, resulting in a gain in the neighborhood of 252, which is approximately 30 dB (1,000 fold). This is confirmed by field tests where the carrier-to-noise-density ratio (C/N0) is typically 45 dB-Hz for GPS but closer to 80 dB-Hz for Iridium.
FIGURE 2. Slant range and spreading loss as a function of orbital altitude and user elevation angle (GSO = geostationary orbit).
Now, we face the drawback of LEO proximity: coverage. Being closer to Earth means that satellites have much smaller footprints as shown in FIGURE 3.
FIGURE 3. Comparison of medium and low Earth orbit satellite distance and footprints (drawn to scale).
FIGURE 4 shows the satellite-footprint radius as a function of orbital altitude and user elevation mask angle. This plot shows the GPS footprint to be threefold larger than Iridium’s, corresponding to nine times more area covered. Hence, to achieve the same coverage as GPS with Iridium’s altitude, a LEO constellation requires an order of magnitude more satellites.
FIGURE 4. Satellite footprint radius as a function of orbital altitude and elevation angle (GSO = geostationary orbit).
Another major difference between LEO and MEO is speed. A GPS satellite completes one Earth revolution every 12 hours, while Iridium does so in only 100 minutes. The shorter the orbital period, the faster the angular rate (also called mean motion) and the more quickly satellites pass overhead. The Earth-centered angular rate of Iridium is seven times faster than GPS.
As a result, users on Earth’s surface see LEO Iridium satellites traverse the local sky in just over 10 minutes compared to hours with satellites in MEO. This characteristic gives rapid changes in geometry and several benefits for navigation.
The swift motion whitens multipath (making it more random, like white noise) as reflections are no longer effectively static over short averaging times. Geometric diversity also leads to effective Doppler positioning as was once leveraged by Transit and now by STL using Iridium. Geometric diversity is also desirable for carrier-phase differential GNSS, allowing for much more rapid resolution of integer cycle ambiguities.
Iridium-Satelles STL Service
As previously mentioned, the STL service has been in operation since May 2016. Many from industry and government are already using this service to achieve a more robust PNT solution. This service will only continue to improve with the Iridium NEXT satellites under deployment — the first 10 were successfully launched in January.
STL is a non-GNSS solution for assured time and location that is highly resilient and physically secure. STL utilizes the Iridium constellation to transmit specially structured time and location broadcasts. Due to their high RF power and signal-coding gain, the STL broadcasts are able to penetrate into difficult attenuation environments, including deep indoors. Like GNSS signals, these broadcasts are specifically designed to allow an STL receiver to obtain precise time and frequency measurements to derive its PNT solutions.
STL is able to augment or serve as a back-up to existing GNSS PNT solutions by providing secure measurements in the presence of high attenuation (deep indoors), active jamming and malicious spoofing. Unlike the MEO GNSS satellites, Iridium uses 48 spot beams to focus its transmissions on a relatively small geographic area. The complex overlapping spot beams of Iridium combined with randomized broadcasts give a unique mechanism to provide location-based authentication that is extremely difficult to spoof.
Two main technical innovations are applied to the existing Iridium quadrature phase-shift keying (QPSK) transmission scheme to facilitate precision measurements. First, the QPSK data at the beginning of an STL burst is manipulated to form a continuous wave (cw) marker, which can be used for burst detection and coarse measurement. Second, the remaining QPSK data in the burst is organized into pseudorandom sequences, reducing the effective information data rate while providing a mechanism for precise measurement via correlation with locally generated sequences.
The processing gain of the sequence correlation operation also enhances the capability of the STL signal to penetrate buildings and other occlusions. STL is designed such that a receiver can reliably decode the bursts and perform precise Doppler and range measurements at attenuations of up to 39 dB relative to unobstructed reception. This is sufficient to penetrate buildings and other occlusions, providing coverage in most deep indoor and urban canyon environments.
In environments where both GNSS and STL time and location fixes are available, the GNSS fixes will generally be more accurate. The key advantage of STL is its ability to provide time and position fixes where GNSS is not available because of occlusions, spoofing or other reasons. In this respect, GNSS and STL can be seen as complementary technologies, and it is apparent that receivers supporting both are highly desirable when practical. An example of a combined GNSS + STL receiver board is shown in FIGURE 5 and is available from Satelles.
To test the signal penetration of STL, trials of the system were undertaken at multiple locations inside an urban high-rise building. For these tests, locations with little or no GPS reception were chosen to measure the impact of such an environment on STL signal reception.
Two GPS receivers were used, a smartphone with assisted GPS and a standalone consumer receiver using Bluetooth communications without assistance data. Similarly, STL was used with and without assistance. For these tests, STL assistance included real-time, out-of-band delivery of satellite clock and orbit data and message payload contents. These test locations ranged from the top (13th) to the bottom (2nd) floor as shown in FIGURE 6.
FIGURE 6. Iridium-based STL test locations. These are indoor and deep attenuation environments where GPS is unavailable.
The results show that only upper floors near windows were able to track at most one to two GPS satellites while lower floors could see none. STL, on the other hand, always experienced strong signals. Even on the lowest floor, with many layers of steel and concrete between the antenna and the sky, the C/N0 from Iridium was between 35 and 55 dB-Hz. GPS, by comparison, is typically between 35 and 50 dB-Hz in an open sky environment.
Indoor Time-Transfer Capability
To evaluate the timing performance of STL in a static, indoor environment, a custom STL receiver board was configured to generate a pulse-per-second (PPS) output. The difference in timing between the STL PPS was then compared to the timing output of a GNSS “truth” reference — in this case, a timing receiver that has nominal timing performance at least an order of magnitude better than the STL-based timing we were attempting to measure.
FIGURE 7 shows the timing difference between the PPS signals generated by the STL receiver and the GNSS receiver, showing the STL ability to provide sub-microsecond timekeeping even in a deep attenuation environment.
FIGURE 7. Iridium-based STL timekeeping results based on data from a 30-day indoor trial. This compares indoor STL timing with a GPS feed from outdoors. This shows STL’s timekeeping to be within 1 microsecond in a deep attenuation environment.
While sub-microsecond timing is sufficient for many applications, higher timing accuracy is desired by some. It has been further demonstrated that STL is capable of achieving sub-100-nanosecond timekeeping in a stand-alone configuration with a rubidium-based STL receiver with an unknown static location indoors.
Indoor Positioning Performance
Unlike the time-transfer capability of STL, positioning requires satellite motion over time to achieve a reasonable 4D time-and-location fix. Therefore, understanding the convergence properties of STL positioning accuracy over time is important to understanding the applicability of STL for various potential uses.
To study these convergence properties, STL data was collected over a 24-hour period in a one-story office environment. The data was then post-processed in a series of trials that each represented a different starting time in the data set — each trial offset to begin 5 seconds ahead of the previous trial’s start time. In this way, the 24-hour data set could be used to generate a statistically significant set of trial runs in which positioning convergence characteristics could be evaluated.
We found out from the results of the post-processed trials that after 10 minutes of convergence, the STL solution had converged to an accuracy of better than 35 meters for 67% of the trials. After sufficient time, typically an accuracy of 20 meters can be achieved in deep attenuation environments such as indoors. The vertical accuracy of STL, in the absence of other measurements or vertical constraints, is comparable to the horizontal accuracy.
Looking Forward
We see the benefit of LEO in navigation with the operational STL using Iridium, where stronger signals allow for operation deep indoors and in other GNSS-challenged environments. Though extremely valuable as a complement to GPS, Iridium lacks the numbers to fully replace GPS as a standalone navigation system in all capacities as only one satellite at a time is typically in view.
However, these numbers may be coming in LEO with the unprecedented scale of the recently announced Broadband constellations of OneWeb, SpaceX, Boeing and others summarized in Table 1. OneWeb’s constellation is nearly as large as the total number of operational satellites in LEO today and is an order of magnitude larger than Iridium. SpaceX’s and Boeing’s proposed constellations each have more than twice the total number of operational satellites in orbit in 2017.
The unparalleled number of satellites in these proposed broadband LEO constellations gives rise to better geometry than any of the GNSS core-constellations in MEO by at least threefold, as shown by FIGURE 8.
FIGURE 8. Comparison of geometric dilution of precision (98th percentile) as a function of constellation size and altitude (MEO = medium Earth orbit; GSO = geostationary orbit).
This plot represents the 98th percentile geometric dilution of precision a user would experience on Earth as a function of constellation size and altitude, assuming a 5-degree elevation mask angle. This stronger geometry allows for relaxation of the signal-in-space user range error, while still matching the user position accuracy of GPS. This enables the use of lower than traditional cost satellite clocks and more amenable orbit determination levels.
When combined with the more benign LEO radiation environment compared to MEO, satellite navigation payloads could be built using commercial off-the-shelf components in place of specialized space-hardened ones, greatly reducing cost. By partnering with these LEO constellation providers, much like Satelles has done with Iridium, a PNT service comparable to GPS could be achieved though with the added benefits of LEO including stronger signals and rapid changes in geometry.
Conclusion
Robust PNT services from LEO are here today, providing augmentation to GPS where GPS isn’t available. The addition of navigation signals from LEO provides a number of benefits. The faster LEO motion provides geometric diversity, giving rise to multipath whitening, faster initialization times for carrier-phase differential GNSS, and Doppler-based positioning.
Perhaps most importantly, LEO constellations have the advantage of being closer to the Earth than the GNSS core constellations in MEO, experiencing less path loss and delivering signals 1,000 times (30-dB) stronger. This makes them more resilient to jamming and more capable in deep attenuation environments such as in urban canyons and indoors.
This extra power allows the LEO-based Satelles STL using Iridium to achieve timekeeping within 1 microsecond and a positioning accuracy of 20 meters, all while deep indoors where GNSS is unavailable. This adds indispensable resilience and security to GNSS that we are increasingly reliant upon, creating a comprehensive satellite navigation system that truly works everywhere.
This PNT service using Iridium is perhaps a sign of things to come. We’ve seen a progression in LEO use since the dawn of the Space Age, namely, an order of magnitude increase in constellation size every 30 years. Transit first offered an occasional position update based on a constellation of six satellites in the 1960s.
Built in the 1990s, Iridium, with an order of magnitude more satellites at 66, now offers global coverage. On the horizon are constellations like OneWeb, which promise the next order of magnitude with 648+ satellites, slated for the 2020s. This most recent scale gives rise to better satellite geometry than GPS today with the added benefits of LEO.
The STL signal using Iridium sets a precedent that could lead to unparalleled navigation services that are robust due to the improved signal strength and precise due to the huge number of LEO satellites coming, each moving quickly and giving the geometric diversity needed to enable fast carrier-phase differential GNSS.
The need for such a service is already clear. It would enable a diversity of future technologies and applications, such as safety-critical autonomous vehicles under development that must operate in challenging urban environments.
Acknowledgments
This article is based on a book chapter to be released in a new generation of GPS “Blue Books” entitled 21st Century Navigation Technologies: Integrated GNSS, Sensor Systems, and Applications to be published by Wiley-IEEE.
The article was also based on the following Institute of Navigation conference publications by the authors:
“Differential and Rubidium Disciplined Test Results from an Iridium-Based Secure Timing Solution” by S. Cobb, D. Lawrence, G. Gutt and M. O’Connor in Proceedings of the 2017 International Technical Meeting of The Institute of Navigation, Monterey, California, 2017.
“Test Results from a LEO-Satellite-Based Assured Time and Location Solution” by D. Lawrence, H.S. Cobb, G. Gutt, F. Tremblay, P. Laplante and M. O’Connor in Proceedings of the 2016 International Technical Meeting of The Institute of Navigation, Monterey, California, 2016.
“Orbital Diversity for Satellite Navigation” by D. Lawrence, H.S. Cobb, G. Gutt, F. Tremblay, P. Laplante and M. O’Connor in Proceedings of ION GNSS 2012, the 25th International Technical Meeting of the Satellite Division of The Institute of Navigation, Nashville, Tennessee, 2012.
“Leveraging Broadband LEO Constellations for Navigation” by T.G.R. Reid, A.M. Neish, T.F. Walter and P.K. Enge in Proceedings of ION GNSS+ 2016, the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation, Portland, Oregon, 2016.
Manufacturers
The unassisted Bluetooth receiver used was a Dual Electronics XGPS150A Universal Bluetooth GPS Receiver; the assisted-GPS smartphone used was a Samsung Galaxy S4. Timing output was evaluated with a Trimble Thunderbolt GNSS timing receiver.
DAVID LAWRENCE is the principal navigation architect for Satelles. In addition to authoring over 20 papers and over 30 patents, Lawrence has developed high-performance navigation software that has been deployed in aircraft landing, precision agriculture, mining, transportation, and machine automation.
H. STEWART COBB is the principal hardware architect for Satelles. Dr. Cobb has made a diverse range of contributions to the PNT community, including inventing and delivering the first commercial implementation of pseudolites as a principal hardware engineer at Novariant.
GREG GUTT is the president and chief technology officer of Satelles. As a graduate student, Gutt Developed ultra-low-noise superconducting sensors for NASA’s Gravity Probe B program. He later went on to become a Boeing technical fellow and is the original principal inventor of the Satelles time and location technology.
MICHAEL O’CONNOR is the chief executive officer of Satelles. As a graduate student, O’Connor developed the world’s first GPS-based precision steering system for farm vehicles. He went on to bring this technology to market with Novariant and helped launch the precision agriculture industry.
TYLER G.R. REID just completed his Ph.D. in the GPS Research Laboratory in the Department of Aeronautics and Astronautics at Stanford University. He is an alumnus of the International Space University and will soon be starting as a research scientist at Ford Motor Company on their autonomous driving team.
TODD WALTER is a senior research engineer in the Department of Aeronautics and Astronautics at Stanford University where he received his Ph.D. in applied physics. His research focuses on implementing high-integrity air navigation systems.
DAVID WHELAN was the vice president and chief technologist for Boeing Defense, Space & Security. Whelan earned his Ph.D. and MS in physics from the University of California Los Angeles and his B.A. from the University of California San Diego.
FURTHER READING
Authors’ Conference Publications
“Differential and Rubidium Disciplined Test Results from an Iridium-Based Secure Timing Solution” by S. Cobb, D. Lawrence, G. Gutt and M. O’Connor in Proceedings of the 2017 International Technical Meeting of The Institute of Navigation, Monterey, California, Jan. 30 – Feb. 1, 2017, pp. 1111–1116.
“Leveraging Commercial Broadband LEO Constellations for Navigation” by T.G.R. Reid, A.M. Neish, T.F. Walter and P.K. Enge in Proceedings of ION GNSS+ 2016, the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation, Portland, Oregon, Sept. 12–16, 2016, pp. 2300–2314 (best presentation award).
“Test Results from a LEO-Satellite-Based Assured Time and Location Solution” by D. Lawrence, H.S. Cobb, G. Gutt, F. Tremblay, P. Laplante and M. O’Connor in Proceedings of the 2016 International Technical Meeting of The Institute of Navigation, Monterey, California, Jan. 25–28, 2016, pp. 125–129.
“Orbital Diversity for Satellite Navigation” by P. Enge, B. Ferrell, J. Bennet, D. Whelan, G. Gutt and D. Lawrence in Proceedings of ION GNSS 2012, the 25th International Technical Meeting of the Satellite Division of The Institute of Navigation, Nashville, Tennessee, 17–21 Sept., 2012, pp. 3834–3846 (best presentation award).
Global Navigation from Low Earth Orbiting Satellites
“Analysis of Iridium-Augmented GPS for Floating Carrier Phase Positioning” by M. Joerger, L. Gratton, B. Pervan and C. E. Cohen in Navigation, Vol. 57, No. 2, Summer 2010, pp. 137–160, doi: 10.1002/j.2161-4296.2010.tb01773.x.
“Overview of IRIDIUM Satellite Network” by K. Maine, C. Devieux and P. Swan in Proceedings of IEEE WESCON’95, the Microelectronics Communications Technology Producing Quality Products Mobile and Portable Power Emerging Technologies Conference (formerly Western Electronics Show and Convention), San Francisco, California, Nov. 7–9, 1995, pp. 483–490, doi: 10.1109/WESCON.1995.485428.
Transit, the U.S. Navy Navigation Satellite System
The Legacy of Transit, a special edition of the Johns Hopkins APL Technical Digest edited by V.L. Pisacane, Vol. 19, No. 1, Jan.–March 1998.
“A History of Satellite Navigation” by B.W. Parkinson, T. Stansell, R. Beard and K. Gromov in Navigation, Vol. 42, No. 1, Spring 1995, pp. 109–164, 10.1002/j.2161-4296.1995.tb02333.x.
“The Navy Navigation Satellite System: Description and Status” by T.A. Stansell, Jr. in Navigation, Vol. 15, No. 3, Fall 1968, pp. 229–243, 10.1002/j.2161-4296.1968.tb01612.x.
GPS and other Global Navigation Satellite Systems
Springer Handbook of Global Navigation Satellite Systems, edited by P.J.G. Teunissen and O. Montenbruck, published by Springer International Publishing AG, Cham, Switzerland, 2017.
Applanix is collaborating on advanced research for autonomous vehicle guidance and control systems with the University of Waterloo Centre for Automotive Research (WatCAR) in Ontario, Canada. Applanix is a Trimble company.
Applanix will provide WatCAR with its positioning and orientation system for testing autonomous guidance and control systems in real-world conditions. Applanix will also provide the Trimble GNSS-inertial board set for integration with car systems and sensors to enable precise positioning.
The Applanix POS LV is a robust, reliable and repeatable positioning solution for on- and off-road vehicles. Applanix technology will be used by WatCAR to assess the performance of the guidance and control systems on board their autonomous vehicles.
The testing will take place in challenging weather conditions and environments including on roads under repair, with lane reductions and closures, are wet or covered in snow, and where there is poor visibility.
An SUV in an anechoic chamber at WatCAR.
Applanix will also provide WatCAR with Trimble on-board GNSS-inertial board set designed for high-performance, high-volume original equipment manufacturer applications. These products, currently used in a variety of autonomous vehicle programs, include the Trimble AP GNSS-inertial board set that includes a high-precision inertial measurement unit.
Small, rugged and low powered, the AP board sets provide the precise positioning needed for autonomous vehicle applications as they navigate their environment. Designed for use on all sizes and types of vehicles, the AP boards feature Trimble’s high-performance precision GNSS receivers and Applanix’ IN-Fusion GNSS-inertial integrated technology that produces uninterrupted position, roll, pitch and true heading measurements of moving platforms. Integrating easily with vehicle sensors, the AP board sets provide precise vehicle control when interacting with a constantly changing environment.
The relationship with WatCAR will aid in improving the core technologies that deliver high-end systems capabilities for a variety of Trimble markets.
The Waterloo Centre for Automotive Research in Canada conducts advanced research to further automotive innovation and competitiveness. From active safety to automated driving through lightweighting and advanced powertrains, 130 faculty researchers comprise the largest university-based automotive activity in the country. Leading-edge studies for industry partners around the world enhance vehicles, components and their materials with new approaches and integration of innovative technologies.
“We are excited to collaborate with the University of Waterloo and WatCAR on this leading research in autonomous vehicle technology,” said Louis Nastro, director of land products at Applanix. “Applanix has been committed to meeting the needs of autonomous vehicle manufacturers for more than a decade, as first demonstrated in the early days of the DARPA Grand Challenge. And today, we are also part of many autonomous vehicle programs deployed worldwide in commercial applications.”
“The Trimble AP products, first introduced in 2009, are designed for use in small, mass market vehicles where size, weight and cost factors are important,” Nastro said. “They have also been designed to easily integrate with the industry’s leading sensors, making them an ideal solution for autonomous vehicle navigation systems and sub-systems.”
“We welcome the opportunity to work with Applanix, a leader in reference systems. Their technology identifies, with very high accuracy, the exact location of our vehicle at all times,” said Ross McKenzie, managing director at WatCAR. “Applanix is a valued industry partner and their team is great to work with. Going forward we anticipate a solution that will enable autonomous vehicles to traverse the real world reliably and safely.”
