M3 Systems is now offering the StellaNGC multi-constellation GNSS simulator based on the National Instruments (NI) vector signal transceiver.
The simulator is designed for the testing of satellite navigation receivers for GPS, GLONASS, Galileo, and EGNOS/WAAS. It is designed to improve performance, scalability, and versatility, and reduce cost over existing navigation test solutions.
GNSS is the predominant technology today for navigation and outdoor positioning. However, given the weakness of GNSS signals, receiver performance is often affected by interference from the local environment and propagation channel conditions. Understanding the effects of this interference is of particular importance not only for existing GNSS signals but also for future signals that will appear with the deployment of new constellations such as Galileo.
To properly characterize receiver performance under varying conditions, the StellaGNC multi-constellation GNSS simulator provides signal generation, signal recording and replay, interference generation, signal and data processing, and complete analysis tools. The StellaNGC simulator is based on the NI vector signal transceiver in PXI for improved performance and full simulation capabilities. For record and playback only, a scaled-down version is also available based on the NI USRP (Universal Software Radio Peripheral). Both options were developed with NI LabVIEW and benefit from the performance and flexibility of the NI RF platform.
The simulator provides a scalable solution that allows easy signal additions through software upgrades, multi-frequency, processing extensions with the addition of FPGAs with NI FlexRIO, and an HDD extension for storage increase. Because the simulator is based on the open PXI standard, the hardware investment can also be extended to other applications, such as simulation, record and playback, or payload simulation.
A panorama from the GNSS tide gauge at Onsala Space Observatory. When satellites pass over the sky, the GNSS tide gauge uses signals direct from the satellite and signals reflected off the sea surface to measure the sea level. Photo: Johan Löfgren
A new way of measuring sea level using satellite navigation system signals, for instance GPS, has been implemented by scientists at Chalmers University of Technology in Sweden. Sea level and its variation can easily be monitored using existing coastal GPS stations, the scientists have shown.
Measuring sea level is an increasingly important part of climate research, and a rising mean sea level is one of the most tangible consequences of climate change. Researchers at Chalmers University of Technology have studied new ways of measuring sea level that could become important tools for testing climate models and for investigating how the sea level along the world’s coasts is affected by climate change.
Johan Löfgren and Rüdiger Haas, scientists at Chalmers Department of Earth and Space Sciences, have developed and tested an instrument that measures the sea level using a GNSS tide gauge.
”The global mean sea level is rising because of climate change, but the change depends on where you are in the world,” says Rüdiger Haas. “We want to be able to make detailed measurements of sea level so that we can understand how coastal societies will be affected in the future.”
When satellites pass over the sky, the GNSS tide gauge uses signals direct from the satellite and signals reflected off the sea surface to measure the sea level. Photo: Johan Löfgren
The GNSS tide gauge uses GPS and GLONASS signals. BeiDou and Galileo will be added in the future.
”We measure the sea level using the same radio signals that mobile phones and cars use in their satellite navigation systems,” says Johan Löfgren. “As the satellites pass over the sky, the instrument ‘sees’ their signals — both those that come direct and those that are reflected off the sea surface.”
Two antennas, covered by small white radomes, measure signals both directly from the satellites and signals reflected off the sea surface. By analyzing these signals together, the sea level and its variation can be measured, up to 20 times per second. The sea level time series is rich in physical phenomena such as tides (caused mostly by the gravitational pull of the Moon and the Sun), meteorological signals (high and low pressure), and signals from climate change. Through advanced signal processing, these signals can be studied further.
The new GNSS tide gauge can measure changes in both land and sea at the same time, in the same location. That means both long-term and short-term land movements (post-glacial rebound and earthquakes) can be taken into consideration.
”Now we can measure the sea level both relative to the coast and relative to the center of the Earth, which means we can clearly tell the difference between changes in the water level and changes in the land,” says Johan Löfgren.
This summer, other high-precision instruments will be installed to work with the Onsala GNSS tide gauge, in collaboration with SMHI, the Swedish Meteorological and Hydrological Institute.
The GNSS tide gauge at Onsala Space Observatory uses signals from satellite navigation systems like GPS to measure the sea level. Photo: Johan Löfgren
”Our tide gauge station will become part of a network of stations along the coast of Sweden that will be able to monitor changes in the water level to millimeter precision well into the future,” says Gunnar Elgered, professor at Chalmers Department of Earth and Space Sciences.
The scientists have also shown that existing coastal GNSS stations, installed primarily for the purpose of measuring land movements, can be used to make sea-level measurements.
”We’ve successfully tested a method where only one of the antennas is used to receive the radio signals. That means that existing coastal GNSS stations — there are hundreds of them all over the world — can also be used to measure the sea level,” says Johan Löfgren.
More about the research
The method is described in two new scientific articles:
This work was previously reported in these publications:
Larson, K.M., J. Lofgren, and R. Haas, Coastal Sea Level Measurements Using A Single Geodetic GPS Receiver, Adv. Space Res., Vol. 51(8), 1301-1310, 2013, doi:10.1016/j.asr.2012.04.017, 2013.
Larson, K.M., R. Ray, F. Nievinski, and J. Freymueller, The Accidental Tide Gauge: A Case Study of GPS Reflections from Kachemak Bay, Alaska, IEEE GRSL, Vol 10(5), 1200-1205, doi:10.1109/LGRS.2012.2236075, 2013.
How a Chip-Scale Atomic Clock Can Help Mitigate Broadband Interference
Small low-power atomic clocks can enhance the performance of GPS receivers in a number of ways, including enhanced code-acquisition capability that precise long-term timing allows. And, it turns out, such clocks can effectively mitigate wideband radio frequency interference coming from GPS jammers. We learn how in this month’s column.
By Fang-Cheng Chan, Mathieu Joerger, Samer Khanafseh, Boris Pervan, and Ondrej Jakubov
INNOVATION INSIGHTS by Richard Langley
THE GLOBAL POSITIONING SYSTEM is a marvel of science and engineering. It has become so ubiquitous that we are starting to take it for granted. Receivers are everywhere. In our vehicle satnav units, in our smart phones, even in some of our cameras. They are used to monitor the movement of the Earth’s crust, to measure water vapor in the troposphere, and to study the effects of space weather. They allow surveyors to work more efficiently and prevent us from getting lost in the woods. They navigate aircraft and ships, and they help synchronize mobile phone and electricity networks, and precisely time financial transactions.
GPS can do all of this, in large part, because the signals emitted by each satellite are derived from an onboard atomic clock (or, more technically correct, an atomic frequency standard). The signals from all of the satellites in the GPS constellation need to be synchronized to within a certain tolerance so that accurate (conservatively stated as better than 9 meters horizontally and 15 meters vertically, 95% of the time), real-time positioning can be achieved by a receiver using only a crystal oscillator. This requires satellite clocks with excellent long-term stability so that their offsets from the GPS system timescale can be predicted to better than about 24 nanoseconds, 95% of the time. Such a performance level can only be matched by atomic clocks.
The very first atomic clock was built in 1949. It was based on an energy transition of the ammonia molecule. However, it wasn’t very accurate. So scientists turned to a particular energy transition of the cesium atom and by the mid-1950s had built the first cesium clocks. Subsequently, clocks based on energy transitions of the rubidium and hydrogen atoms were also developed. These initial efforts were rather bulky affairs but in the 1960s, commercial rack-mountable cesium and rubidium devices became available. Further development led to both cesium and rubidium clocks being compact and rugged enough that they could be considered for use in GPS satellites. Following successful tests in the precursor Navigation Technology Satellites, the prototype or Block I GPS satellites were launched with two cesium and two rubidium clocks each. Subsequent versions of the GPS satellites have continued to feature a combination of the two kinds of clocks or just rubidium clocks in the case of the Block IIR satellites.
While it is not necessary to use an atomic clock with a GPS receiver for standard positioning and navigation applications, some demanding tasks such as geodetic reference frame monitoring use atomic frequency standards to control the operation of the receivers. These standards are external devices, often rack mounted, connected to the receiver by a coaxial cable—too large to be embedded inside receivers.
But in 2004, scientists demonstrated a chip-scale atomic clock, and by 2011, they had become commercially available. Such small low-power atomic clocks can enhance the performance of GPS receivers in a number of ways, including enhanced code-acquisition capability that precise long-term timing allows. And, it turns out, such clocks can effectively mitigate wideband radio frequency interference coming from GPS jammers. We learn how in this month’s column.
“Innovation” is a regular feature that discusses advances in GPS technology and its applications as well as the fundamentals of GPS positioning. The column is coordinated by Richard Langley of the Department of Geodesy and Geomatics Engineering, University of New Brunswick. He welcomes comments and topic ideas. Write to him at lang @ unb.ca.
Currently installed Local Area Augmentation System (LAAS) ground receivers have experienced a number of disruptions in GPS signal tracking due to radio frequency interference (RFI). The main sources of RFI were coming from the illegal use of jammers (also known as personal privacy devices [PPD]) inside vehicles driving by the ground installations. Recently, a number of researchers have studied typical properties of popular PPDs found in the market and have concluded that the effect of PPD interference on the GPS signal is nearly equivalent to that of a wideband signal jammer, to which the current GPS signal is most vulnerable. This threat impacts LAAS or any ground-based augmentation system (GBAS) in two ways:
Continuity degradation — as vehicles with PPDs pass near the GBAS ground antennas, the reference receivers lose lock due to the overwhelming noise power.
Integrity degradation — the code tracking error will increase when the noise level in the tracking loop increases.
Numerous interference mitigation techniques have been studied for broadband interference. The interference mitigation methods can be separated according to the two fundamental stages of GPS signal tracking: the front-end stage, in which automatic gain control and antenna nulling/beam forming techniques are relevant, and the baseband stage, where code and carrier-tracking loop algorithms and aiding methods are applicable.
In our current work, the baseband strategy and resources that are practically implementable at GBAS ground stations are considered. Among those resources, we focus on using atomic clocks to mitigate broadband GNSS signal interference. For GPS receivers in general, wide tracking loop bandwidths are used to accommodate the change in signal frequencies and phases caused by user dynamics. Unfortunately, wide bandwidths also allow more noise to enter into the tracking loop, which will be problematic when wideband inference exists. The general approach to mitigate wideband interference is to reduce the tracking loop bandwidth. However, a reference receiver employing a temperature-compensated crystal oscillator (TCXO) needs to maintain a minimum loop bandwidth to track the dynamics of the clock itself, even when all other Doppler effects are removed. The poor stability of TCXOs fundamentally limits the potential to reduce the tracking loop bandwidth. This limitation becomes much less constraining when using an atomic clock at the receiver, especially in the static, vibration-free environment of a GBAS ground station.
Integrating atomic clocks with GPS/GNSS receivers is not a new idea. Nevertheless, the practical feasibility of such integration remained difficult until recent advancements in atomic clock technology, such as commercially available compact-size rubidium frequency standards or, more recently, chip-scale atomic clocks (CSACs). Most of the research using atomic clock integrated GPS receivers aims to improve positioning and timing accuracy, enhance navigation system integrity, or coast through short periods of satellite outages. In these applications, the main function of the atomic clock is to improve the degraded system performance caused by bad satellite geometries. As for using narrower tracking loop bandwidths to obtain better noise/jamming-resistant performance, the majority of work in this area has focused on high-dynamic user environments with extra sensor aiding, such as inertial navigation systems, pseudolites, or other external frequency-stable radio signals. These aids alone do not permit reaching the limitation of tracking loop bandwidth reduction since the remaining Doppler shift from user dynamics still needs to be tracked by the tracking loop itself. Our research intends to explore the lower end of the minimum tracking loop bandwidth for static GPS/GNSS receivers using atomic clocks.
High-frequency-stability atomic clocks naturally reduce the minimum required bandwidth for tracking clock errors (since clock phase random variations are much smaller). We have conducted analyses to obtain the theoretical minimum tracking loop bandwidths using clocks of varying quality. Carrier-phase tracking loop performance under deteriorated C/N0 conditions (that is, during interference) was investigated because it is the most vulnerable to wideband RFI. The limitations on the quality of atomic clocks and on the receiver tracking algorithms (second- or third-order tracking loop bandwidths) to achieve varying degrees of interference suppression at the GBAS reference receivers are explored. The tracking loop bandwidth reductions and interference attenuations that are achievable using different qualities of atomic clocks, including CSACs and commercially available rubidium receiver clocks, are also discussed in this article.
In addition to the theoretical analyses, actual GPS intermediate frequency (IF) signals have been sampled using a GPS radio frequency (RF) frond-end kit, which is capable of utilizing external clock inputs, connected to a commercially available atomic clock. The sampled IF data are fed into a software receiver together with and without simulated wideband interference to evaluate the performance of interference mitigation using atomic clocks. The wideband interference is numerically simulated based on deteriorated C/N0. The actual tracking errors generated from real IF data are used to validate the system performance predicted by the preceding broadband interference mitigation analyses.
Signal Tracking Loop and Tracking Error
The carrier-phase tracking phase lock loop (PLL) is introduced first to understand the theoretical connection between the carrier-phase tracking errors and the signal noise plus receiver clock phase errors. A simplified PLL is shown in FIGURE 1 with incoming signals set to zero. In the figure, n(s), c(s), and δθ(s) are receiver white noise, clock phase error or clock disturbance, and tracking loop phase error respectively, with s being the Laplace transform parameter. G(s) is the product of the loop filter F(s) and the receiver clock model 1/s.
FIGURE 1. Simplified tracking loop diagram.
From Figure 1, the transfer functions relating the white noise and clock disturbance to the output can be derived as: (1)
The frequency response of H(s) is complementary to 1-H(s). Therefore, the PLL tracking performance is a trade-off between the noise rejection performance and the clock disturbance tracking performance.
Total PLL errors resulting from different error sources are presented as phase jitter, which is the root-mean-square (RMS) of resulting phase errors. Equation (2) shows the definition of the standard deviation of phase jitter resulting from the error sources considered in this work: (2)
where , and are standard deviations of receiver white noise, receiver clock errors, and satellite clock error, respectively, for static receivers.
The standard deviation for each of the clock error sources can be evaluated using the frequency response of the corresponding transfer function and power spectral densities (PSDs). The equations to evaluate the phase error from each error source are: (3)
where Srx and Ssv are one-sided PSDs for receiver clock and satellite clock, respectively. Bw is the bandwidth of the tracking loop and Tc is the coherent integration time.
Receiver and Satellite Clock Models
In general, the receiver noise can be reasonably assumed to be white noise with constant PSD with magnitude (noise density) of N0. However, it is not the case for clock errors. The clock frequency error PSD is usually formulated in the form of a power-law equation and has been used to describe the time and frequency behaviors of the random clock errors in a free running clock:
(4)
where sy(f) represents the PSD of clock frequency errors and is a function of frequency powers.
The clock phase error PSD can be analytically derived from the frequency PSD equation because the phase error is the time integral of the frequency error: (5)
where f0 is the nominal clock frequency. The h coefficients of the clock phase error PSD are the product of the h coefficients from the clock frequency error PSD and the nominal frequency.
We have adopted the PSD clock error models in our work to perform tracking loop performance analysis. The PSD of the CSAC is derived from an Allan deviation figure published by the manufacturer and is shown in FIGURE 2. We took three piecewise Allan deviation straight lines, which are slightly conservative, and converted them to a PSD.
FIGURE 2. Allan deviations for chip-scale atomic clock.
Three PSDs of clock error models are listed in TABLE 1, which represent spectrums of the well known TCXO, the CSAC, and a rubidium standard. Phase noise related h0 and h1 coefficients in the CSAC model are assumed to be the same as the TCXO because they can’t be obtained from the Allan deviation figure. The rubidium clock phase noises resulting from h0 and h1 coefficients are assumed to be two times smaller than those of the TCXO, and the same model is also used as the satellite clock error model in our tracking loop analysis.
TABLE 1. Coefficients of power-law model.
Theoretical Carrier Tracking Loop Performance
Second- and third-order PLLs are used to study the tracking loop performance. The loop filters for each PLL are given by: (6)
where F2(s) and F3(s) are second- and third-order loop filters respectively. Typical coefficients for the second- and third-order loop filters are a2 = 1.414; wo,2 = 4×Bw,2 × a2/[(a2)2+1]; a3 = 1.1; b3 = 2.4; wo,3 = Bw,3/0.7845.Bw,2 and Bw,3 are the second- and third-order tracking loop bandwidths accordingly.
As stated earlier, three error sources are considered for static receivers. Using the clock error models described earlier, the contribution of different error sources to phase jitter is a function of PLL tracking bandwidth. The resulting phase tracking errors from different error sources are evaluated based on Equation (3) and shown in FIGURE 3.
FIGURE 3. Phase error contribution from different error sources.
The third-order PLL performance using 2-, 1-, 0.5- and 0.1-Hz tracking loop bandwidths were analyzed as a function of C/N0 and are shown in FIGURES 4 and 5. For each selected bandwidth, three different qualities of receiver clocks were analyzed, and a conventional 15-degree performance threshold was adopted. The second-order PLL performs similarly to the third-order PLL. However, the phase jitter tends to be more biased when the tracking loop bandwidth becomes smaller. This phenomenon will be observed later on using signal data for performance validation. Therefore, only the third-order loop performance analysis is shown in Figures 4 and 5. It is obvious from these two figures that the minimum tracking loop bandwidth for a TCXO receiver PLL is about 2 Hz, and the PLL can work properly only while C/N0 is above 24 dB-Hz.
FIGURE 4 Tracking loop performance analysis for 2- and 1-Hz loop bandwidth.FIGURE 5. Tracking loop performance analysis for 0.5- and 0.1-Hz loop bandwidth.
As for the receiver using atomic clocks, CSAC and a rubidium frequency standard in our analysis, the PLL bandwidth can be reduced down to at least 0.1 Hz while C/N0 is above 15 dB-Hz.
Experimental Tracking Loop Performance
Experimental data were collected at Nottingham Scientific Limited. The experiment was conducted using a GPS/GNSS RF front end with a built-in TCXO clock. The RF front end also has the capability of accepting atomic clock signals through an external clock input connector to which the CSAC (see Photo) was connected during data collection. All data (using the built-in TCXO clock or the CSAC) were sampled at a 26-MHz sampling rate and at a 6.5-MHz IF with 2-MHz front-end bandwidth and four quantization levels.
A MatLab-coded software defined receiver (SDR) was used to process collected IF samples for tracking loop performance validation. TCXO phase jitters resulting from different tracking loop bandwidths are shown in FIGURE 6 for a typical second-order PLL under a nominal C/N0, which is about 45 dB-Hz. A 45-degree loss-of-lock threshold was adopted (three times larger than the standard deviation threshold used in an earlier performance analysis). In our work, all code tracking delay lock loops (DLLs) are implemented using a second-order loop filter with 20-millisecond coherent integration time and 0.5-Hz loop bandwidth without any aiding. The resulting phase jitters in the figure become biased when the tracking loop bandwidth is reduced. This observed phenomenon implies that a second-order PLL time response cannot track the clock dynamics when the loop bandwidth approaches the minimum loop bandwidth (where loss of lock occurs).
FIGURE 6. Second-order PLL phase jitter using TCXO.
The same IF data was re-processed by the SDR using the third-order PLL with the same range of tracking loop bandwidths. The resulting phase jitters are shown in FIGURES 7 and 8. There is no observable phase jitter bias before the PLLs lose lock in the figures. These results demonstrate that a third-order PLL performs better in terms of capturing the clock dynamics when the tracking loop bandwidth is reduced close to the limitation. Therefore, only the third-order PLL will be considered further.
FIGURE 7. Third-order PLL phase jitter using TCXO.FIGURE 8. Third-order PLL phase jitter using CSAC.
The performance of the TCXO PLL can be evaluated from the results in Figure 7. It demonstrates that the minimum loop bandwidth is 2 Hz, which is consistent with the previous analysis shown in figure 4. However, the minimum bandwidth using the CSAC is shown to be 0.5 Hz in Figure 8. This result does not meet the performance predicted by the analysis, which shows that the working bandwidth can be reduced to 0.1 Hz.
Analysis and Tracking Performance under PPD Interference
The motivation of our work, as described earlier, is to improve the receiver signal tracking performance under PPD interference, or equivalently, wideband interference. We carried out a simple analysis first to understand how much signal deterioration a GBAS ground receiver could expect. A 13-dBm/MHz PPD currently available on the market was used to analyze the signal deterioration based on the distance between the PPD and the GBAS ground receiver. A simple analysis using a direct-path model shows that noise power roughly 30 dB higher than the nominal noise level (about -202 dBW/Hz) could be experienced by the GBAS ground receiver if the nearest distance is assumed to be 0.5 kilometers. In this case, any wideband interference mitigation method to address PPD interference has to handle C/N0 as low as 10 to 15 dB-Hz.
Gaussian distributed white noises were simulated and added on top of the original IF samples, then re-quantized to the original four quantization levels to mimic the PPD interference signal condition. A 20-dB higher noise level was simulated to demonstrate the effectiveness of this signal deterioration technique.
The tracking loop performance using the third-order PLL under low C/N0 conditions was evaluated using the IF sampling and PPD interference simulation technique just described. The evaluation results show that the minimum PLL bandwidth using the TCXO is still 2 Hz. This result is roughly consistent with a previous analysis showing a 24-dB-Hz C/N0 limitation using 2-Hz tracking bandwidth. The PLL using the CSAC performs better than that using the TCXO, which is expected.
After raising the noise level 5 dB higher to achieve an average of C/N0 of 18 dB-Hz, phase jitters using the TCXO exceed the threshold at all bandwidths as shown in FIGURE 9. The same magnitude of noise was also added to the CSAC IF samples. The resulting phase jitters are shown in FIGURE 10, which demonstrates that the minimum bandwidth is 1 Hz for this deteriorated signal condition. Any further increase in noise level will result in loss of lock for PLLs using a CSAC at all tracking bandwidths.
FIGURE 9. Phase jitter using TCXO under 18 dB-Hz C/N0.FIGURE 10. Phase jitter using CSAC under 18 dB-Hz C/N0.
Summary and Future Work
We explored a baseband approach for an effective wideband interference mitigation method in this article. We have presented the theoretical analysis and actual data validation to study the possible improvement of the PLL tracking performance under PPD interference, which has been experienced by LAAS ground receivers.
The limitations of reducing PLL tracking loop bandwidths using different qualities of receiver clocks have been analyzed and compared with the experimental results generated by processing IF samples using an SDR. We conclude that the PLL tracking performance using a TCXO is consistent between theoretical prediction and data validation under both nominal and low C/N0 conditions. However, the PLL tracking performance using the CSAC was not as good as the analysis prediction under both conditions.
In our future work, to understand the reason for the tracking performance inconsistency using the CSAC, we will carefully examine and evaluate the hardware components in line between the external clock input and the IF sampling chip. In this way, we will exclude the clock performance degradation due to any hardware incompatibility.
Other types of high quality clocks, such as extra-low-phase-noise oven-controlled crystal oscillators and low-phase-noise rubidium oscillators, will also be tested to explore the limitation of PLL tracking bandwidth reduction. If the results using other clocks exhibit good consistency between performance analysis and data validation, it is highly possible that the CSAC clock error model mis-represents the available commercial products.
In our future work, we will also consider simulating PPD interference more closely to the real scenario, by adding analog interference signals on top of GPS/GNSS analog signals before taking digital IF samples.
Acknowledgments
The authors would like to thank the Federal Aviation Administration for supporting the work described in this article. Also, the authors would like to extend their thanks to all members of the Illinois Institute of Technology NavLab and to the collaborators from Nottingham Scientific Limited for their insightful advice. This article is based on the paper “Using a Chip-scale Atomic Clock-Aided GPS Receiver for Broadband Interference Mitigation” presented at ION GNSS+ 2013, the 26th International Technical Meeting of the Satellite Division of The Institute of Navigation held in Nashville, Tennessee, September 16–20, 2013.
Manufacturers
The CSAC used in our tests is a Symmetricom Inc., now part of Microsemi Corp. (www.microsemi.com), model SA.45s. We used a Nottingham Scientific Ltd. (www.nsl.eu.com) Stereo GPS/GNSS RF front end with the MatLab-based SoftGNSS 3.0 software from the Danish GPS Center at Aalborg University (gps.aau.dk).
FANG-CHENG CHAN is a senior research associate in the Navigation Laboratory of the Department of Mechanical and Aerospace Engineering at the Illinois Institute of Technology (IIT) in Chicago. He received his Ph.D in mechanical and aerospace engineering from IIT in 2008. He is currently working on GPS receiver integrity for Local Area Augmentation System (LAAS) ground receivers, researching GPS receiver interference detection and mitigation to prevent unintentional jamming using both baseband and antenna array techniques, and developing navigation and fault detection algorithms with a focus on receiver autonomous integrity monitoring or RAIM.
MATHIEU JOERGER obtained a master’s in mechatronics from the National Institute of Applied Sciences in Strasbourg, France, in 2002, and M.S. and Ph.D. degrees in mechanical and aerospace engineering from IIT in 2002 and 2009 respectively. He is the 2009 recipient of the Institute of Navigation Bradford Parkinson award, which honors outstanding graduate students in the field of GNSS. He is a research assistant professor at IIT, working on multi-sensor integration, on sequential fault-detection for multi-constellation navigation systems, and on relative and differential RAIM for shipboard landing of military aircraft.
SAMER KHANAFSEH is a research assistant professor at IIT. He received his M.S. and Ph.D. degrees in aerospace engineering at IIT in 2003 and 2008, respectively. He has been involved in several aviation applications such as autonomous airborne refueling of unmanned air vehicles, autonomous shipboard landing, and ground-based augmentation systems. He was the recipient of the 2011 Institute of Navigation Early Achievement Award for his contributions to the integrity of carrier-phase navigation systems.
BORIS PERVAN is a professor of mechanical and aerospace engineering at IIT, where he conducts research focused on high-integrity satellite navigation systems. Prof. Pervan received his B.S. from the University of Notre Dame, M.S. from the California Institute of Technology, and Ph.D. from Stanford University.
ONDREJ JAKUBOV received his M.Sc. in electrical engineering from the Czech Technical University (CTU) in Prague in 2010. He is a postgraduate student in the CTU Department of Radio Engineering and he also works as a navigation engineer for Nottingham Scientific Limited in Nottingham, U.K. His research interests include GNSS signal processing algorithms and receiver architectures.
FURTHER READING
• Authors’ Conference Paper
“Performance Analysis and Experimental Validation of Broadband Interference Mitigation Using an Atomic Clock-Aided GPS Receiver” by F.-C. Chan, S. Khanafseh, M. Joerger, B. Pervan and O. Jakubov in the Proceedings of ION GNSS+ 2013, the 26th International Technical Meeting of the Satellite Division of The Institute of Navigation, Nashville, Tennessee, September 16–20, 2013, pp. 1371–1379.
“Three Satellite Navigation in an Urban Canyon Using a Chip-scale Atomic Clock” by R. Ramlall, J. Streter, and J.F. Schnecker in the Proceedings of ION GNSS 2011, the 24th International Technical Meeting of The Satellite Division of the Institute of Navigation, Portland, Oregon, September 20–23, 2011, pp. 2937–2945.
“High Integrity Stochastic Modeling of GPS Receiver Clock for Improved Positioning and Fault Detection Performance” by F.-C. Chan, M. Joerger, and B. Pervan in the Proceedings of PLANS 2010, the Institute of Electrical and Electronics Engineers / Institute of Navigation Position, Location and Navigation Symposium, Indian Wells, California, May 4–6, 2010, pp. 1245–1257, doi: 10.1109/PLANS.2010.5507340.
“Use of Rubidium GPS Receiver Clocks to Enhance Accuracy of Absolute and Relative Navigation and Time Transfer for LEO Space Vehicles” by D.B. Cox in the Proceedings of ION GNSS 2007, the 20th International Technical Meeting of the Satellite Division of The Institute of Navigation, Fort Worth, Texas, September 25–28, 2007, pp. 2442–2447.
• Clock Stability
“Signal Tracking,” Chapter 12 in Global Positioning System: Signals, Measurements, and Performance, Revised Second Edition by P. Misra and P. Enge. Published by Ganga-Jamuna Press, Lincoln, Massachusetts, 2011.
“Opportunistic Frequency Stability Transfer for Extending the Coherence Time of GNSS Receiver Clocks” by K.D Wesson, K.M. Pesyna, Jr., J.A. Bhatti, and T.E. Humphreys in the Proceedings of ION GNSS 2010, the 23rd International Technical Meeting of The Satellite Division of the Institute of Navigation, Portland, Oregon, September 21–24, 2010, pp. 2937–2945.
“Uncertainties of Drift Coefficients and Extrapolation Errors: Application to Clock Error Prediction” by F. Vernotte, J. Delporte, M. Brunet, and T. Tournier in Metrologia, Vol. 38, No. 4, 2001, pp. 325–342, doi: 10.1088/0026-1394/38/4/6.
• Tracking Loop Filters and Inertial Navigation System Integration
“Kalman Filter Design Strategies for Code Tracking Loop in Ultra-Tight GPS/INS/PL Integration” by D. Li and J. Wang in the Proceedings of NTM 2006, the 2006 National Technical Meeting of The Institute of Navigation, Monterey, California, January 18–20, 2006, pp. 984–992.
“Satellite Signal Acquisition, Tracking, and Data Demodulation,” Chapter 5 in Understanding GPS: Principles and Applications, Second Edition, E.D. Kaplan and C.J. Hegarty, Editors. Published by Artech House, Norwood, Massachusetts, 2006.
“GPS and Inertial Integration”, Chapter 7 in Global Position System: Theory and Applications, Vol. 2, by R.L. Greenspan. Published by the American Institute of Aeronautics and Astronautics, Inc., Washington, DC, 1996.
“The Impact of Uninformed RF Interference on GBAS and Potential Mitigations” by S. Pullen, G. Gao, C. Tedeschi, and J. Warburton in the Proceedings of ION GNSS 2012, the 25th International Technical Meeting of the Satellite Division of The Institute of Navigation, Nashville, Tennessee, September 17–21, 2012, pp. 780–789.
“Survey of In-Car Jammers-Analysis and Modeling of the RF Signals and IF Samples (Suitable for Active Signal Cancelation)” by T. Kraus, R. Bauernfeind, and B. Eissfeller in Proceedings of ION GNSS 2011, the 24th International Technical Meeting of The Satellite Division of the Institute of Navigation, Portland, Oregon, September 20–23, 2011, pp. 430–435.
Tallysman Wireless, Inc., is offering a family of very low power, compact, high-performance GNSS antennas for precision, commercial, and military applications.
Based in Ottawa, Canada, Tallysman Wireless, is a designer and manufacturer of high-performance GNSS, Iridium, and Globalstar antennas and associated components.
The TW4327 and TW4329 are low-power GPS L1 + GLONASS G1 antennas that feature current consumption of 1.75 mA typically and parametrically invariant performance over a supply range from 2.5V to 12V.
The TW4327 o ffers a 21-dB gain minimum, and the TW4329 includes a narrow pre-fi lter to prevent front end saturation by near out-of-band interfering signals.
Both antennas are more tolerant to detuning eff ects caused by the operational environment, thanks to a 40% thicker patch element that provides wider bandwidth than conventional antennas. These antennas are also very compact (38mm x 38mm x 14.4mm), making them ideal for use in a wide range of locations.
The TW4027 and TW4029 are equivalent antennas for reception of GPS L1 signals.
“These products are ideal for any battery operated applications where low power is a pre-requisite,” said Gyles
Panther CEO of Tallysman Wireless, “and the wider patch element bandwidth will minimize detuning in non-ideal
environments, such as in covert applications.”
Tallysman Wireless has recently added an authorized distributor of its products for Russia (Aurora Mobile Technologies), and another distributor for Asia (Advanced Information Technology, Inc.), for the countries of Vietnam, Hong Kong, Singapore, China, Indonesia, and India.
Spectracom, a business of the Orolia Group, has extended its global service capability through a partnership with EZU Technologies. Joining Spectracom service centers in North America and Europe, EZU Technologies will support Spectracom users throughout the Asia-Pacific region from its facility in Hong Kong. Initially, services will include equipment calibration and repair services. Over time, more capability will be added to deliver Spectracom’s full range of services in the region.
Spectracom’s portfolio of GNSS signal management solutions include a variety of services to ensure their customers gets the most out of their application for positioning, navigation and timing. “We understand our customer’s needs for fast access to services. Our strong growth in Asia, particularly for GNSS simulation and enterprise-class timing, will be supported by localizing services in the region,” said Thierry Delhomme, general manager, Spectracom Europe.
This new service center is the first of several partnerships to deliver global services in support of Spectracom solutions. Lisa Withers, Spectracom President and CEO, said, “We are pleased to expand our existing partnership with EZU Technologies to develop a regional service hub. This will enhance the local service provided by our strong set of local distributors and resell partners throughout the region.”
Spirent Communications today introduced the GSS6300M range of multi-channel GPS and multi-GNSS simulators for receiver integrators, application developers, aftercare and production testing environments. This entry-level test system readily enables laboratory evaluation of GPS performance across different locations and routes, Spirent said. In addition to being easy-to-use even for non-GPS experts, the GSS6300M range features competitive pricing for engineering teams looking to integrate positioning functionality to new classes of consumer electronic devices.
The GSS6300M is a “one-box” solution with everything required to start testing immediately and can be controlled from a tablet or smartphone, or via remote commands across multiple interfaces. It enables a variety of fundamental test and compliance to industry standard. Users can create custom trajectories using a Google Maps interface to help evaluate receiver performance.
The GSS6300M offers the same preeminent signal quality as other Spirent test systems, which are used by governments and space agencies around the world. High fidelity test equipment ensures the highest user experiences, leading to improved customer satisfaction, reduced product returns and greater market success for integrators and application teams.
“Positioning is of key importance to a wide range of new applications and consumer devices. As navigation and GPS test experts, Spirent wants to help developers build high-performing positioning functionality into their systems quickly and easily,” said John Pottle, marketing director of Spirent Positioning Technology. “Spirent provides test equipment that our customers rely on to achieve accurate results they can trust. The GSS6300M continues this tradition and is priced to be widely accessible.”
The GSS6300M is designed to for the huge and growing range of applications and technologies that incorporate location features — from vehicles and mobile devices to wearable technology, security tracking and other new market segments. In addition to GPS, the GSS6300M fully supports GLONASS, BeiDou and Galileo, the Russian, Chinese and European navigation systems.
Calling it an “unprecedented and deeply worrying total disruption . . . [that] shook the industry,” Locata Corporation reiterated its call for redundant terrestrial systems to back up GNSS in the wake of the April 1 11-hour GLONASS system outage.
Nunzio Gambale, Locata CEO, said “We have been telling the industry for years that you cannot have a critically important capability like GPS without also having a backup! What is Plan B if the satellite systems fail? What replaces the space signal when there is a problem? If anyone needed a sign to understand why Locata has spent years inventing and developing the world’s first local terrestrial equivalent of the GPS system, then last week’s meltdown of a complete global satellite navigation system is it. This event should terrify every nation, government, and company that depends on navigation satellites for their business or, in some cases, their very lives.”
The navigation and timing functions of the global positioning systems underpin the world’s banking systems, stock exchanges, digital TV and Internet, cell phone networks, and, in some cases, the national electricity supply, Locata pointed out. GPS, in particular, plays a crucial role in transportation, shipping, and logistics, serving as the enabling technology for critical functions like air traffic control. Reliability is therefore not just important; it is essential across all applications. Locata, the Resilient Navigation and Timing Foundation (RNTF) in Washington, D.C., and others have persistently called attention to the need for redundant terrestrial systems that will back up expensive, vulnerable, and aging global satellite navigation constellations while simultaneously providing the local control and resiliency that satellite-based systems cannot deliver.
Professor Chris Rizos of the School of Civil and Environmental Engineering at the University of New South Wales stated that “This catastrophic failure of one of the world’s two global satellite navigation constellations is a wakeup call for all of us. We ignore the possibility of these ‘Black Swan’ events at our own peril.”
The GLONASS disruption was felt around the world, immediately upon its origination, especially in professional applications, such as tractor automation for farming, machine control and robotics in mining and heavy industry, and in the national infrastructure used by surveyors and industry across many countries.
“This shows just how interlinked the physical and cyber worlds have now become,” added Professor Brett Biddington, a space and cybersecurity expert from the School of Computer and Security Science at Edith Cowan University, Australia. “The prospect of a software glitch, whether unintentional or intentional, seems highly likely [as a cause for the failure]. If it was a deliberate attack, however, it points to a changing face of warfare where the real enemy may be impossible to detect and deter until very damaging strikes, such as an attack on the GPS system, have already taken place.
“The vital point here is that this is no longer just a question for scientists and technologists. A locally controlled backup system for this essential signal is a national policy question of the highest order.”
Locata Corporation and other industry authorities have long testified on global satellite navigation vulnerabilities and the need for diverse technology options to strengthen and back up GPS, GLONASS, and other systems. Locata developed a robust solution and has been awarded a sole-source contract by the U.S. Air Force (USAF) to provide its terrestrially based alternative positioning for military applications where GPS has been completely jammed. The first wide-area Locata system is being deployed now at the White Sands Missile Range in New Mexico. The USAF demonstrated that the White Sands Locata network delivers what has been extremely high accuracy over a 2,500-square mile area, positioning aircraft flying up to 35 miles away to an accuracy of better than six inches.
A pair of LocataLite transmit antennas overlook a section of the White Sands Missile Range blanketed by the Locata high-precision ground-based positioning system.
“There is no other technology that can do this, and it’s delivered in the complete absence of GPS,” continued Gambale. “What is being demonstrated at White Sands is that Locata supplies precisely the same function as GPS, even when there is no GPS available. That’s exactly what you need if the satellites fail.
“If this event had been a GPS failure instead of a GLONASS failure – and it could very easily have been – then the entire world would have plunged into a catastrophe. This event is the navigation equivalent of a ‘close call moment,’ and from here on out no one can even question that this is a really serious problem that must be addressed. Another industry expert recently told me, ‘If there was a sustained GPS outage, it would cause a global financial nuclear winter from which it would take us decades to recover.’”
Gambale concluded, “We need action to develop local backups like Locata around places like airports and other strategically important areas – now! We must not wait until we are faced with another seemingly impossible event like a complete satellite constellation failure. We may not dodge this bullet a second time.”
Locata terrestrial positioning technologies complement GPS by setting up ground-based transmitters, called LocataLites, to create a local constellation called a LocataNet. Once properly deployed, Locata’s unique nanosecond-accurate TimeLoc system synchronizes the network, which allows it to replicate the positioning capabilities of GPS, locally. LocataNets operate today in environments ranging from small warehouses to open-cut mines, wide-area aircraft approach-and-landing systems, and wider areas for aircraft and unmanned aerial vehicle (UAV) uses.
The GSG-51 GNSS signal generator provides a fast and cost-effective solution for production testing for Galileo and other GNSS. It emulates a single GNSS signal and can be upgraded for Galileo, as well as to increase the channel count, add receiver trajectory control, and add advanced features such as SBAS (WAAS, EGNOS,MSAS, or GAGAN), white noise generation, or multipath simulation. Its main application is a simple but very fast manufacturing test, to assure that the assembly is correct, that the antenna is properly connected, and that the receiver can receive and identify a satellite signal, for instance, in mobile phones with integrated GNSS receivers.
With a wide RF level range from –65 to –160 dBm, the sensitivity of all types of GNSS receivers can be verified with a minimum of delay. The 60-dB of extra power from normal test scenarios allows for splitting the signal many times.
Yesterday we posted news of an 11-hour downtime for the full GLONASS constellation, due to an upload of bad ephemerides. Coincidentally, during that 11-hour period, the mass-market chip company Broadcom was conducting multi-constellation receiver tests in Asia. Frank van Diggelen, Broadcom’s chief GNSS scientist and vice president says, “We have definitive data to show how a multi-constellation receiver survives such an outage.”
Here are the pictures, and the story they tell.
Test data coincident with the GLONASS ephemeris disruption of April 1 and 2 showing conclusively how a GPS/GLONASS/QZSS/BEIDOU receiver survives the complete disruption of one of the constellations.
On April 2 at 1:00 a.m. Moscow time, bad ephemeris was uploaded to all satellites (see chart at the bottom of this story).
There are two receivers shown here, from two different manufacturers, both in smartphones. The yellow dots are for a GPS/GLONASS receiver; the blue dots are from the Broadcom 47531 receiver which tracks GPS/GLONASS/QZSS/BeiDou signals simultaneously. The 47531 receiver includes logic to use redundant measurements to check the validity of all measurements. It successfully identified and removed the bad GLONASS ephemeris 100 percent of the time, as can be seen by the continuity and accuracy of the positions.
Here is the satellite outage chart from yesterday’s story. All GLONASS satellites were restored to healthy state after the 11-hour interruption.
Current plot from the Roscosmos GLONASS Information-Analytical Centre. Things are almost back to normal this morning.
By Mirko Stanisak, Mark Bitter, and Thomas Feuerle
INNOVATION INSIGHTS by Richard Langley
GPS = SAFER FLIGHT. While reviewing material for an article celebrating the 25th anniversary of the launch in February 1989 of the first Block II or operational GPS satellite, I was yet again annoyed by many articles on the Web stating that GPS only became available for civil use after the launch of this satellite. Some sources get closer to the truth when they say that GPS was opened for civil use in 1983, following the shoot-down of the Korean Airlines Flight 007. In fact, GPS was designed to serve the needs of both the military and civil communities from the outset. A government memo from April 1973 clearly states: “Civil user needs should be considered in the design of the spaceborne equipment.”
One of the first demonstrations of the use of GPS for aircraft navigation occurred in July 1983, when a Sabreliner business jet was flown in stages from Cedar Rapids, Iowa, to the Paris Air Show, flying only when a sufficient number of the experimental or Block I satellites were in view. The first standalone GPS receivers certified for aviation use (with Receiver Autonomous Integrity Monitoring or RAIM) became available by the mid-1990s. But already the Federal Aviation Administration had been looking into the development of a system to provide higher accuracies and better integrity than that afforded by standalone receivers. In 1994, the FAA announced the development of the Wide Area Augmentation System, its brand of a system generically known as satellite-based augmentation. Geostationary satellites transmit corrections and integrity information to GPS receivers, permitting GPS use for en route navigation all the way down to traditional Category I approach and landing. CAT I approaches can be flown down to a decision height of 61 meters (200 feet). WAAS was declared operational on July 10, 2003, but enhancements to the system continue. Japan, Europe, and India also have operational SBAS based on GPS.
Ground-based GPS augmentation was first developed for maritime applications with the U.S. Coast Guard’s low-frequency system coming on line in the mid-1990s. Also in the mid-1990s, the FAA began the development of the Local Area Augmentation System, generically known as a ground-based augmentation system (GBAS), to provide aircraft with approach and landing capabilities from CAT I down through CAT II (30-meter or 100-foot decision height) and CAT III (no decision height but certain visual range minima) using a VHF datalink. Initial CAT I systems are being operated at Bremen, Germany, and at Newark Liberty International Airport and Houston George Bush Intercontinental Airport.
While a GPS-based GBAS will definitely offer improved navigation services for aircraft, might these services be even better if the systems were to use satellites from other constellations besides GPS? In this month’s column, we look at a straw-man concept for modifying the GBAS protocols to accommodate multiple constellations and the results of preliminary tests using GPS, GLONASS, and Galileo simultaneously.
“Innovation” is a regular feature that discusses advances in GPS technology and its applications as well as the fundamentals of GPS positioning. The column is coordinated by Richard Langley of the Department of Geodesy and Geomatics Engineering, University of New Brunswick. He welcomes comments and topic ideas. Write to him at lang @ unb.ca.
Ever since the declaration of Full Operational Capability (FOC) of the U.S. Global Positioning System in April 1995, GPS has dominated satellite navigation, especially in aviation applications. By contrast, the Russian GLONASS system cannot be used in western aviation because no approval guidelines exist for GLONASS equipment. Thus GPS has been the de-facto standard in aviation for years.
However, within the last few years, major changes have evolved in the field of GNSS, providing a wide variety of useable satellite navigation systems. The European Union launched its Galileo project, which will provide global multi-frequency services in the near future. China is upgrading its BeiDou system (formerly called Compass) to provide global coverage with more medium-Earth-orbit (MEO) satellites. The operators of GPS and GLONASS have started modernization programs that will enable multi-frequency operations in the future, too. Therefore, a large number of usable satellites and signals from multiple systems will soon be available.
In aviation, almost all phases of flight can be assisted by satellite navigation systems nowadays. The most challenging phase of flight with respect to accuracy, continuity, availability, and integrity is the approach and landing phase. The Ground Based Augmentation System (see FIGURE 1; courtesy of the European Organization for Civil Aviation Equipment) allows precision approaches to be performed using satellite navigation. It uses a VHF data link to broadcast differential GNSS corrections, integrity information, and approach definitions to approaching aircraft. These aircraft combine the differential corrections with their own GNSS measurements, calculate a GBAS-corrected position solution, and determine path deviations based on the selected approach.
FIGURE 1. GBAS principle. (Source: EUROCAE WG 28, ED-114)
From a technical perspective, GBAS can use either GPS or GLONASS for differential corrections. For this, the International Civil Aviation Organization (ICAO) Standards and Recommended Practices (SARPs) include GPS and GLONASS side by side. On the other hand, some standardization documents (for example, those from RTCA) are limited to GPS only, effectively excluding GLONASS from being used in the western world. Nevertheless, Russian GBAS systems provide differential corrections for GPS and GLONASS, and are expected to be certified in Russia in the near future. Additional GNSS such as Galileo or BeiDou are not yet included within these documents, as these systems are not approved for aviation use themselves. This article will focus on how a multi-constellation GBAS with GPS, GLONASS, and Galileo could work.
GBAS installations can provide multiple services for different kinds of operation, based on GNSS L1 corrections only. On the one hand, the differentially corrected positioning service (DCPS) is intended to be a generic service for high accuracy positioning. On the other hand, two different GBAS approach services have been defined. GBAS Approach Service Type C (GAST-C) allows Category I (CAT I) procedures and is already in operation. GAST-D is still under development and will enable precision approaches and landings down to CAT II/III minima once certified. To mitigate all possible hazards, GAST-D will require some additional broadcast messages.
VHF Data Broadcast
The VHF Data Broadcast (VDB) is used to communicate binary GBAS messages to approaching aircraft. It operates in the VHF band (108.025 – 117.975 MHz) and uses time-division multiple access (TDMA) to allow the operation of multiple GBAS ground stations on a single frequency. As shown in FIGURE 2, VDB uses UTC time to have a common time frame. Two frames are transmitted each second, lasting 0.5 seconds each. Within each frame, eight slots with durations of 62.5 milliseconds can be used for transmission. Binary application data is encoded using a differentially encoded eight-phase-shift-keying modulation (D8PSK) and a symbol rate of 10,500 symbols per second. With three bits transmitted per symbol, up to 31,500 bits per second can be transmitted. Each slot can contain up to 222 bytes of binary application data. Usually, only a subset of slots is allocated to a particular ground facility. This way, multiple GBAS ground facilities can share a common VDB frequency.
Within each slot, multiple VDB messages can be transmitted as application data. The coding of information in VDB messages is defined in the RTCA’s GNSS-Based Precision Approach Local Area Augmentation System (LAAS) Signal-in-Space Interface Control Document (ICD) and depends on the VDB message type. (LAAS is the U.S. GBAS.) Currently, message types (MT) 1, 2, 3, 4 and 11 are defined. Figure 2 is derived from this document.
Message Type 1 – MT1. Within VDB Message Type 1, differential corrections based on 100-second smoothing are transmitted. These corrections are required by all GBAS approach services (GAST-C and GAST-D). Aside from the differential corrections, additional information for the first broadcast satellite is transmitted. This includes an ephemeris cyclic redundancy check (CRC), mitigating the effects of wrongly received GNSS navigation data, and the Issue of Data (IOD) flag, indicating the time of applicability for the ephemeris data to be used. To transmit this information for all satellites, the satellite for which differential corrections are transmitted first has to be alternated continuously.
Each MT1 message can contain up to 18 pseudorange- and range-rate corrections for individual satellites. Nevertheless, it is possible to link two consecutive MT1 messages using the Additional Message Flag (AMF). The value of this parameter indicates whether this is a single message (0), or the first (1) or second (3) part of a linked MT1 message. Up to 36 differential corrections can be transmitted using two consecutive VDB time slots with 18 corrections each.
All MT1 measurement blocks must be transmitted at least once per frame. The maximum transmission rate is once per slot for all measurement blocks.
Message Type 2 – MT2. VDB Message Type 2 contains station and integrity parameters such as the coordinates of the reference point to which all differential corrections refer. MT2 messages can include (next to a “core” MT2 message) multiple Additional Data Blocks (ADBs) to transmit information required for different GBAS services. At the moment, the Additional Data Blocks 1, 3, and 4 are defined.
ADB1 contains the maximum distance to the reference point at which the corrections may be used (Dmax) as well as parameters to calculate the remaining risk of incorrect GNSS ephemeris data (Kmd,e). Within ADB3, additional information required for GAST-D is transmitted. ADB4 implements the VDB authentication feature. If this ADB is broadcast by a ground facility, MT2 messages must be transmitted first and contain additional indications about which VDB slots are allocated to the ground facility.
MT2 messages must be transmitted at least each 20th frame, but may be repeated up to once per frame.
Message Type 3 – MT3. The VDB Message Type 3 is a fill message, which is only used in conjunction with the GBAS authentication feature (MT2, ADB4). Among other things, this feature requires a minimum slot occupancy of at least 95 percent. Thus, MT3 messages are broadcast only by ground facilities that support the authentication feature and are completely ignored by airborne GBAS receivers.
Message Type 4 – MT4. With VDB Message Type 4, approach information can be broadcast to approaching aircraft. A pilot can select a specific approach by simply tuning to a given channel number.
Currently, GBAS only uses Instrument Landing System look-alike straight-in approaches called Final Approach Segments (FAS). Each FAS represents one approach. This way, a single GBAS ground facility can provide multiple approaches for all runways of an airport. All approaches must be broadcast at least once per 20 consecutive frames.
Message Type 11 – MT11. The VDB Message Type 11 provides differential corrections in a way very similar to MT1 messages. The main difference is that MT11 corrections are based on 30-second smoothing, which is required for GAST-D service. As for MT1, all MT11 measurement blocks must be transmitted at least once per frame.
Enhancements for GBAS with Galileo
At the moment, the GBAS standardization documents include information on GPS, GLONASS, and SBAS ranging sources. No information on Galileo or other constellations has been added yet. Thus, to include Galileo for GBAS, some Galileo-specific experimental additions to the standards are necessary. These proposed modifications have been made in such a way as to keep as close to the other system standards as possible to preserve consistency. This way, hardly any new functionality is added, but additional satellites can be used. The additional Galileo signals (E5a, E5b, E6) are not used at the moment; however, they might be highly beneficial for multi-frequency applications in the future.
All modifications presented here are purely experimental and will most probably not be exactly the same as those in future standards documents. Nevertheless, they provide a way to test Galileo together with GPS and GLONASS for GBAS on an experimental basis.
Ranging Source ID. The Ranging Source ID uniquely addresses a single satellite. It is used in MT1 and MT11 to transmit the differential corrections and other information for each ranging source. In ICAO Annex 10, Standards and Recommended Practices, the Ranging Source ID is defined for GPS, GLONASS, and SBAS only. To provide Galileo corrections as well, an experimental mapping for Galileo satellites was added; see TABLE 1.
TABLE 1. GBAS Ranging Source IDs.
In this way, up to 36 Galileo satellites can be addressed.
Navigation Data. Galileo provides two different sets of navigation data. The I/NAV data corresponds to the Safety-of-Life (SoL) service and is broadcast on E1 and E5b. The F/NAV data corresponds to the Open Service (OS) and is broadcast on E5a. In order to remain as close as possible to the legacy navigation systems, we selected the I/NAV navigation data for use, as it is broadcast on the E1 frequency and can thus be received with an L1-only GNSS receiver.
The navigation data is primarily used in VDB MT1. For the first transmitted correction in this message, the ephemeris set that shall be used in the aircraft is identified via the Issue of Data (IOD) field. To be consistent with the GPS ephemeris, we used Galileo’s IODnav parameter.
Together with the identification of the navigation data, a CRC parameter is transmitted in MT1 for the first satellite within the differential corrections. This parameter ensures that the receiver as well as the ground facility use identical navigation data for all calculations. The CRC algorithm uses the raw navigation data to generate a distinct CRC value.
For GPS and GLONASS, two ephemeris masks are defined. These masks ensure that only information relevant for GBAS processing are covered by the CRC. For Galileo, a similar mask had to be designed.
Additional Data Blocks in MT2. Within VDB MT2, station parameters and integrity information are transmitted. Some parameters for the over-bounding of possible ephemeris errors are specific to each satellite navigation system.
To extend MT2 to Galileo, parameters for the DCPS, GAST-C, and GAST-D must be added for Galileo. For downward compatibility, these parameters cannot be included in the existing Additional Data Blocks beside the existing parameters. Thus, a new Additional Data Block (ADB5) was defined on an experimental basis. This Additional Data Block is dedicated to Galileo and is structured as shown in TABLE 2. The coding of all values corresponds to the coding of the parameters for the existing systems.
TABLE 2. Additional Data Block 5 in Message Type 2 for Galileo parameters.
Optimized VDB Transmission Scheme
Having available a large number of ranging sources for differential corrections, the VHF VDB is a bottleneck for the transmission of this data. To demonstrate this, we first consider the number of visible satellites that there will be in the future. This leads to construction rules for an optimal VDB transmission scheme, which allows transmitting the maximum number of differential corrections.
Number of Satellites Available. To demonstrate the number of differential corrections enabled by the different systems in the future, we computed the number of visible satellites over a day for a stationary GNSS receiver in Braunschweig, Germany. Even though only four Galileo satellites were in orbit at that time, up to 26 different satellites (GPS, GLONASS, and Galileo) were in view simultaneously. Keeping in mind the preliminary Galileo constellation, it is obvious that more than 30 satellites will be available simultaneously in the future — considering only GPS, GLONASS, and Galileo. Adding BeiDou satellites for GBAS would further boost these numbers.
The broadcast of such a large number of differential corrections is limited by the capacity of the VDB and thus by the number of slots assigned to a GBAS ground facility. The number of assigned slots for a facility should be limited as far as possible to be able to use the same frequency for other GBAS ground facilities. Thus, the available capacity must be used as effectively as possible.
Number of Bytes Required. Each VDB message is framed by a message block header (6 bytes) and the message block CRC (4 bytes).
The length of each message depends on the message type and the amount of information to be transmitted. The resulting length for a message of each type is given in TABLE 3.
TABLE 3. Size of different VDB message types (including message block header and CRC). Variable length message types are dependent on the number of corrections, N.
VDB Constraints. A GBAS ground facility must transmit the VDB data following some constraints. These are:
MT2 messages (including all Additional Data Blocks required) must be transmitted at least each 20th frame (that is, every 10 seconds).
If authentication is required, each MT2 message must be transmitted in the first slot assigned to the GBAS ground facility.
All differential corrections (both MT1 and MT11) must be transmitted at least once in each frame. However, it is possible to split the differential corrections into two adjacent slots using the Additional Message Flags in MT1 and MT11 messages.
Within each MT1 message, the ephemeris decorrelation parameter (Peph), the Issue of Data (IOD), and the ephemeris CRC is transmitted for the first satellite in the message. Thus, the first satellite must be alternated in order to broadcast the ephemeris information for all satellites.
Approach definitions are transmitted in MT4 messages. All MT4 messages must be transmitted within at least each 20th slot.
Based on these constraints, a VDB encoding scheme has been developed, which allows us to fulfill all the requirements listed above while optimizing the number of differential corrections that can be transmitted. Even though it is optimized for GAST-D-like services (including authentication parameters, MT11 messages, and experimental Galileo extensions), it can be used for legacy GAST-C systems, too.
Rules for Optimal VDB Transmission. To fulfill the requirement for the MT2 message to be transmitted first, a complete MT2 message must be transmitted each 20th frame at the beginning of the first slot assigned. If no MT2 message has to be transmitted, an MT4 message is transmitted instead. Thus, all messages are arranged in proper order by three simple rules:
MT2 (each 20th frame) or MT4 (otherwise)
MT11 (all corrections; can be split into two messages)
MT1 (all corrections; can be split into two messages).
Additionally, two more rules must be fulfilled. On the one hand, if supporting the authentication feature, each slot in which the ground facility may transmit VDB data must be filled to at least 95 percent. For this, MT3 null messages may be used to ensure that each slot is filled sufficiently. On the other hand, an additional rule for MT1 messages is necessary if more than three slots are assigned to the GBAS ground facility. In this case, to maximize the number of differential corrections the MT1 messages may be transmitted in the last two assigned slots only. This rule is necessary because the Additional Message Flag is limited to two slots for differential corrections.
Using this transmission scheme, the number of differential corrections is maximized while fulfilling the minimum requirements on the VDB data. Even in case of the maximum number of differential corrections, MT4 approach definitions can still be broadcast. However, in this case, the number of transmittable FAS segments is limited to 19. If more approaches (or different approach types such as Terminal Area Paths (TAPs)) have to be transmitted, the VDB generation scheme must be adapted.
Number of Transmittable Corrections. Using the optimized transmission scheme explained earlier, the number of transmittable corrections can be calculated easily for different numbers of assigned slots for GAST-C as well as for GAST-D services (see TABLE 4).
TABLE 4. Number of differential corrections that can be broadcast.
The exact distribution of VDB messages for the maximum number of differential corrections (18) is shown in FIGURE 3 for an MT1/MT11 configuration and two assigned slots.
FIGURE 3. VDB messages for two slots and 18 satellites (MT1 and MT11).
Experimental Realization of Multi-Constellation GBAS
The experimental GBAS multi-constellation extensions described earlier have been implemented in software for further testing. As these enhancements are purely experimental and might change in the future, we have ensured that these definitions can be changed easily.
Navigation Software. The Institute of Flight Guidance at Technische Universität Braunschweig has been developing an experimental navigation framework for many years. This software, called TriPos, can handle and combine different navigation technologies. TriPos can be used for simulations, post-processing of recorded data, and even for live (online) processing. It is written in C++ and supports various platforms.
The navigation framework can be extended easily. Originally, only GPS was supported within the software, but support for GLONASS and Galileo as well as augmentation systems like SBAS and GBAS were added over the past few years. Additionally, the software handles GNSS data of multiple frequencies internally and can thus be used for multi-constellation and multi-frequency applications. TriPos includes decoders for the binary protocols of most GNSS receivers currently available.
For GBAS research, two components can be simulated using the software. On the one hand, the Ground Facility simulation calculates the differential corrections and provides simulated VDB data. On the other hand, the GBAS receiver simulation emulates the behavior of an airborne GBAS receiver and uses VDB data and GNSS measurements to calculate a GBAS solution. Both simulations can use either recorded data in post-processing or live data for online-processing. This allows complete simulation of GBAS.
Multi-Constellation GBAS Ground Facility Simulation. The GBAS ground facility simulation uses raw binary data from multiple stationary GNSS receivers to calculate binary VDB data. The simulation can be freely configured to process either live or pre-recorded GNSS data. Even though it features all algorithms required by the standards, it does not contain additional monitor algorithms at the moment.
Nevertheless, it can provide a valid VDB signal-in-space (SIS), which can be used by GBAS receivers and simulation tools (such as Eurocontrol’s PEGASUS tool). The ground facility simulation supports legacy GBAS CAT-I (GAST-C) as well as GAST-D (including all additional VDB information required) using GPS and GLONASS. Support for Galileo has been added according to the experimental definitions described earlier. In addition to FAS data blocks, the ground facility simulation is also capable of providing curved approaches using TAP data blocks.
Multi-Constellation Airborne GBAS Receiver Simulation. The GBAS receiver simulation has been used for various GBAS-related projects. It supports GAST-C as well as GAST-D and can be configured flexibly to use GPS, GLONASS, and/or Galileo (using the experimental enhancements as described earlier). For GAST-D, all airborne monitoring algorithms required are present. Thus, the aircraft-specific parameters (for example for the airborne geometry screening) can be configured together with the other parameters.
Flight Trials
The practicability of the multi-constellation GBAS approach has been tested in flight trials. To ensure that all four Galileo satellites were in view and capable of providing valid data during our trials, an orbit prediction tool and the Notice Advisory to Galileo Users (NAGU) service of the European GNSS Service Center (GSC) were used prior to the flight.
The data processing configuration is shown in FIGURE 4 and includes the GBAS simulation components explained earlier. All processing is done in real time while recording all data for later post processing.
FIGURE 4. Schematic data processing for the flight experiments (ground components in orange, airborne components in blue).
Ground Processing. On the ground, two Septentrio AsteRx3 GNSS receivers connected to two roof-top antennas were used. The GNSS receivers were connected to the GBAS ground facility simulation via a network and provided binary GPS, GLONASS, and Galileo raw measurements with an update rate of 2 Hz as well as navigation data. Using this data, the ground facility simulation generated binary VDB data. The GBAS ground facility simulation was configured to generate multi-constellation GAST-D VDB data for a three-slot configuration. All required messages (MT1, MT2 including all required ADBs, MT3, MT4 and MT11) were generated and sent to the telemetry facility via the network.
Telemetry. Official VHF data broadcasts operate in a frequency band between 108 and 118 MHz, which is reserved for authorized aviation applications. However, for our experimental system, an alternative data link was used. The Institute of Flight Guidance operates a full-duplex telemetry system to share data between ground and aircraft. Even though the operating frequencies are different, the telemetry system allows the generated binary VDB data to be transmitted to research aircraft. The airborne telemetry receiver outputs data as if it were a VDB receiver to allow us to switch between a real VDB receiver and the telemetry receiver easily.
Research Aircraft. The Institute of Flight Guidance operates the research aircraft of the Technische Universität Braunschweig. The Dornier Do 128-6 with the call sign D-IBUF (see FIGURE 5) is a twin-engine turboprop aircraft without a pressurized cabin and has been used multiple times for GBAS-related research over the years.
FIGURE 5. Research aircraft D-IBUF (Dornier Do 128-6).
The research aircraft allows us to flexibly integrate experimental equipment for specific flight trials. For the multi-constellation GBAS flights, a JAVAD Delta GNSS receiver (capable of multiple constellations and frequencies), a telemetry receiver, and an experimental cockpit display were installed temporarily.
Airborne Processing. The online GBAS receiver simulator uses GNSS data from the JAVAD Delta GNSS receiver together with the VDB data received via telemetry. The receiver was configured to output raw GPS, GLONASS, and Galileo measurements with an update rate of 10 Hz. The simulator was configured to use this data to calculate a multi-constellation GAST-D solution. Based on the selected approach definition, the resulting information (deviations, distance to threshold, and so on) was displayed in the cockpit using an experimental cockpit display.
Results. The flight test was conducted in the evening of November 6, 2013 (16:52 – 17:58 UTC), at Research Airport Braunschweig (EDVE). We performed five approaches with a 10 nautical mile final segment. The flight path as calculated by the GBAS receiver subsystem is shown in FIGURE 6.
FIGURE 7 shows the number of satellites used for the GBAS receiver simulation, and distinguishes between the different satellite navigation systems used. Up to 22 satellites have been used simultaneously for GBAS processing, including up to 10 GPS satellites, eight GLONASS satellites, and four Galileo satellites.
FIGURE 7. Number of satellites used by the multi-constellation GBAS receiver simulation.
Even though no certified GBAS equipment was used for the flight trials, FIGURE 8 shows the resulting vertical and lateral protection levels (VPL and LPL) of the online multi-constellation GBAS receiver simulation. Both values fluctuate due to the differences between 100- and 30-second smoothing position solutions, which have to be added to the protection levels for GAST-D. Nevertheless, both sets of values remain clearly below the corresponding Alert Limits (FAS Lateral Alarm Limit (FASLAL): 40 meters, FAS Vertical Alarm Limit (FASVAL): 10 meters). A valid GAST-D service was achieved continuously.
FIGURE 8. Vertical and lateral protection levels (VPL and LPL).
FIGURE 9 shows a vertical integrity diagram, commonly known as a Stanford plot, for the integrity of the multi-constellation GBAS simulation. This plot shows the Vertical Protection Level (VPL) as determined by the GBAS receiver simulation against the actual Vertical Position Error (VPE). The Vertical Position Error is a direct measure for the Vertical Navigation System Error (V-NSE). This has been determined using a precise point positioning reference trajectory. Both values are normalized by the current VAL as these values change during the approaches. During the flight, the GBAS online processing ran at a rate of 10 Hz, resulting in 43,670 GAST-D epochs and an availability of 100 percent.
FIGURE 9. Normalized vertical Stanford plot of flight trials (GAST-D using GPS, GLONASS, and Galileo). Color scale indicates number of occurrences.
Of course, these results must not be misinterpreted as a multi-constellation GBAS performance assessment. The ground facility simulation was highly experimental and lacked any kind of long-term analysis. Even the GNSS antennas used do not meet formal requirements. However, aside from a quantitative judgment, these results show the practicability of this multi-constellation GBAS approach on an experimental basis.
Conclusion and Outlook
In this article, experimental extensions to GBAS have been developed to support GPS, GLONASS, and Galileo simultaneously. Based on these extensions, an optimized VDB transmission scheme has been created. In this way, the number of transmittable differential corrections could be maximized. Using flight trials, the multi-constellation GBAS concept has successfully been verified. The experimental airborne GBAS subsystem was able to calculate a valid GBAS solution including GPS, GLONASS, and Galileo satellites continuously.
It has been shown that multi-constellation GBAS is possible from a purely technical perspective. On the other hand, neither operational nor approval aspects for satellite navigation systems other than GPS have been addressed yet. Additionally, further testing would be necessary to ensure the compatibility with legacy GPS-only GBAS equipment. However, in theory, all modifications for Galileo are backward compatible. Nevertheless, it has to be assured that certified GBAS multi-mode receivers only use the GPS part of the VDB data and are not disturbed by additional VDB messages or additional ranging sources, for example. The required tests are planned for the future.
The operational benefit of multi-constellation GBAS systems cannot be foreseen yet. A certification for this will take several years and could only be addressed by the GBAS community after the completion of the GAST-D certification. Most probably, the use of GNSS signals on multiple frequencies could provide a highly improved GBAS service and will allow much more operational benefit. Many of the satellite navigation systems have already introduced additional frequencies, including signals in the protected L5 aviation band. The use of multiple frequencies for satellite navigation in aviation can remove most ionospheric errors effectively and mitigate a major source of uncertainty. Thus, multi-constellation GBAS can just be seen as a preliminary step on the way towards multi-frequency GBAS. The concepts and infrastructure described in this article will serve as a basis for more research in this area.
Acknowledgments
Most of our work on multi-constellation GBAS was done within the research project “Bürgernahes Flugzeug,” which was established in 2009 and is partly funded by the German federal state of Lower Saxony. This is gratefully acknowledged by the authors. Additionally, the authors would like to thank all colleagues involved for constructive discussions and their support. This article is based on the paper “Mulitple Satellite Navigation for the Ground Based Augmentation System” presented at ITM 2014, The Institute of Navigation 2014 International Technical Meeting, held in San Diego, California, January 27-29, 2014.
MIRKO STANISAK is a research assistant at the Institute of Flight Guidance (IFF) at the Technische Universität (TU) Braunschweig in Germany. He received his diploma in mechanical engineering (Dipl.-Ing.) in 2009 from TU Braunschweig.
MARK BITTER holds a Dipl.-Ing. in mechanical engineering from TU Braunschweig and has been employed as a research engineer at TU Braunschweig IFF since 2003.
THOMAS FEUERLE received his Dipl.-Ing. in mechanical engineering in 1997 from TU Braunschweig. He joined the TU Braunschweig IFF in May 1997. Since 2005, he has been the leader of the Air Traffic Management Team at the IFF. In April 2010, he completed his Ph.D. dissertation at TU Braunschweig.
FURTHER READING
• Authors’ Conference Paper
“Multiple Satellite Navigation Systems for the Ground Based Augmentation System,” by M. Stanisak, M. Bitter, and T. Feuerle in Proceedings of ITM 2014, the 2014 International Technical Meeting of The Institute of Navigation, San Diego, California, January 27–29, 2014, pp. 254–264.
• Standards Documents
Aeronautical Communications, Vol. 1, Radio Navigation Aids, Annex 10 to the Convention on International Civil Aviation, International Standards and Recommended Practices, International Civil Aviation Organization, Montreal, Draft Version, May 2010.
GNSS-Based Precision Approach Local Area Augmentation System (LAAS) Signal-In Space Interface Control Document (ICD), DO-246D, RTCA Special Committee 159, Global Positioning Systems, RTCA Inc. Washington, D.C., December 2008.
Minimum Operational Performance Standards for GPS Local Area Augmentation System Airborne Equipment, DO-253C, RTCA Special Committee 159, Global Positioning Systems, RTCA Inc. Washington, D.C., December 2008.
Minimum Operational Performance Specification for Global Navigation Satellite Ground Based Augmentation System Ground Equipment to Support Category I Operations, ED-114, EUROCAE Working Group 28 on Global Navigation Satellite System, European Organisation for Civil Aviation Equipment, Malakoff, France, September 2003.
• GBAS Research and Development
“Conception, Implementation and Validation of a GAST-D Capable Airborne Receiver Simulation” by M. Stanisak, R. Schork, M. Kujawska, T. Feuerle, and P. Hecker in Proceedings of ION GNSS 2012, the 25th International Technical Meeting of the Satellite Division of The Institute of Navigation, Nashville, Tennessee, September 17–21, 2012, pp. 250–257.
“Initial GBAS Experiences in Europe” by A. Lipp, A. Quiles, M. Reche, W. Dunkel, and S. Grand-Perret in Proceedings of ION GNSS 2005, the 18th International Technical Meeting of the Satellite Division of The Institute of Navigation, Long Beach, California, September 13–16, 2005, pp. 2911–2922.
The authors test three mass-market design drivers on a chip developed expressly for a new role as a combined GPS and Galileo consumer receiver: the time-to-first-fix for different C/N0, for hot, warm, and cold start, and for different constellation combinations; sensitivity in harsh environments, exploiting a simulated land mobile satellite multipath channel and different user dynamics; and power consumption strategies, particularly duty-cycle tracking.
By Nicola Linty, Paolo Crosta, Philip G. Mattos, and Fabio Pisoni
The two main GNSS receiver market segments, professional high-precision receivers and mass-market/consumer receivers, have very different structure, objectives, features, architecture, and cost. Mass-market receivers are produced in very high volume — hundreds of millions for smartphones and tablets — and sold at a limited price, and in-car GNSS systems represent a market of tens of millions of units per year. The reason for these exploding markets can be found not only in the improvements in electronics and integration, but also in the increasing availability of new GNSS signals. In coming years, with Galileo, QZSS, BeiDou, GPS-L1C, and GLONASS-CDMA all on the way, the silicon manufacturer must continue the path towards the fully flexible multi-constellation mass-market receiver.
Mass-market receivers feature particular signal processing techniques, different from the acquisition and tracking techniques of standard GNSS receivers, in order to comply with mobile and consumer devices’ resources and requirements. However, a limited documentation is present in the open literature concerning consumer devices’ algorithms and techniques; besides a few papers, all the know-how is protected by patents, held by the main manufacturers, and mainly focused on the GPS L1 C/A signal. We investigate and prove the feasibility of such techniques by semi-analytical and Monte Carlo simulations, outlining the estimators sensitivity and accuracy, and by tests on real Galileo IOV signals.
To understand, analyze, and test this class of algorithms, we implemented a fully software GNSS receiver, running on a personal computer. It can process hardware- and software-simulated GPS L1 C/A and Galileo E1BC signals, as well as real signals, down-converted at intermediate frequency (IF), digitalized and stored in memory by a front-end/bit grabber; it can also output standard receiver parameters: code delay, Doppler frequency, carrier-to-noise power density ratio (C/N0), phase, and navigation message. The software receiver is fully configurable, extremely flexible, and represents an important tool to assess performance and accuracy of selected techniques in different circumstances.
Code-Delay Estimation
The code-delay estimation is performed in the software receiver by a parallel correlation unit, giving as output a multi-correlation with a certain chip spacing. This approach presents some advantages, mostly the fact that the number of correlation values that can be provided is thousands of times greater, compared to a standard receiver channel. Use of multiple correlators increases multipath-rejection capabilities, essential features in mass-market receivers, especially for positioning in urban scenarios. The multi-correlation output is exploited to compute the received signal code delay with an open-loop strategy and then to compute the pseudorange.
In the simulations performed, the multi-correlation has a resolution of 1/10 of a chip, which is equivalent to 30 meters for the signals in question; to increase the estimate accuracy, Whittaker-Shannon interpolation is performed on the equally spaced points of the correlation function belonging to the correlation peak.
The code-delay estimate accuracy is reported in Figures 1 and 2. The results are obtained with Monte Carlo simulations on simulated GNSS signals, with sampling frequency equal to 16.3676 MHz. In particular, a GPS L1 C/A signal is considered, affected by constant Doppler frequency equal to zero for the observation period, to avoid the effect of dynamics. The figures show the standard deviation of the code estimation error, that is, the difference between the estimated code delay and the true one, expressed in meters (pseudorange error standard deviation) for different values of C/N0. To evaluate the quality of the results, the theoretical delay locked loop (DLL) tracking jitter is plotted for comparison, as
where Bn is the code loop noise bandwidth, Rc is the chipping rate, Bfe is the single sided front-end bandwidth, Tc is the coherent integration time, and c is the speed of light.
In the two figures, the red curve shows the theoretical tracking jitter for a DLL, which can be considered as term of comparison for code-delay estimation. To correlate the results, a E-L spacing equal to D = 0.2 chip is chosen, and the code-delay error values of the software receiver simulation are filtered with a moving average filter. By averaging 0.5 seconds of data (for example, L = 31 values spaced 16 milliseconds), an equivalent closed-loop bandwidth of about 1 Hz can be obtained:
In particular, in Figure 1, a coherent integration time equal to 1 millisecond (ms) and 16 non-coherent sums are considered, while in Figure 2 a coherent integration time equal to 4 ms and 16 non-coherent sums, spanning a total time T=64 ms, are considered. In both cases, the software receiver results are extremely good for high C/N0. The code-delay error estimate is slightly higher than its equivalent in the DLL formulation. The open-loop estimation error notably increases in the first case below 40 dB-Hz due to strong outliers, whose probability of occurrence depends on the C/N0. In fact, this effect is smoothed in the second case, where the coherent integration time is four times larger, thus improving the signal-to-noise ratio.
Nevertheless, the comparison between open loop multi-correlation approach and closed loop DLL is difficult and approximate, because the parameters involved are different and the results are only qualitative.
Doppler Frequency Estimation
In the particular case of the software receiver developed here, the residual Doppler frequency affecting the GNSS signal is estimated by means of a maximum likelihood estimator (MLE) on a snapshot of samples, exploiting open-loop strategy. In fact, despite the higher standard deviation of the frequency error (jitter), open-loop processing offers improved tracking sensitivity, higher tracking robustness against fading and interference, and better stability when increasing the coherent integration time. In addition, the open-loop approach does not require the design of loop filters, avoiding problems with loop stability. A certain number of successive correlator values, computed in the multiple correlations block, are combined in a fast Fourier transform (FFT) and interpolated.
Figure 3 shows the root mean square error (RMSE) of the frequency estimate versus signal
C/N0, obtained collecting 16 coherent accumulations of 4 ms of a Galileo E1B signal, then computing a 16 points FFT spanning a time interval of 64 ms, and finally refining the result with an interpolation technique. Three different curves are shown, corresponding respectively to:
the RMSE derived from simulations, carried out with GNSS data simulated with the N-FUELS signal generator;
a semi-analytical estimation, exploiting the same algorithm;
the Cramer-Rao lower bound (CRLB) for frequency estimation, shown as
where fs is the sampling frequency.
Figure 3. Doppler frequency estimate RMSE versus C/N0 in super-high resolution with T=64 ms, comparison between theoretical and simulated results.
A well-known drawback is the so-called threshold effect. Below a certain C/N0, the frequency estimate computed with MLE suffers from an error, and the RMSE increases with respect to the CRLB.
Mass-Market Design Drivers
Once we have analyzed the features of some mass-market algorithms with a software receiver, we can move toward the performance of a real mass-market device, to compare results and confirm improvements brought by the new Galileo signals, so far mainly known from a theoretical point of view.
A recent survey identified three main drivers in the design of a mass-market receiver, coming directly from user needs, and solvable in different ways.
Time-to-first-fix (TTFF) corresponds to how fast a position, velocity, and time (PVT) solution is available after the receiver is powered on, that is, the time that a receiver takes to acquire and track a minimum of four satellites, and to obtain the necessary information from the demodulated navigation data bits or from other sources.
Capability in hostile environments, for example while crossing an urban canyon or when hiking in a forest, is measured in terms of sensitivity. It can be verified by decreasing the received signal strength and/or adding multipath models.
Power consumption of the device. GNSS chipset is in general very demanding and can produce a not-negligible battery drain.
We analyzed these three drivers with a commercial mass-market receiver and with the software receiver.
Open-Sky TTFF Analysis
TTFF depends on the architecture of the receiver, for example the number of correlators or the acquisition strategy, on the availability of assistance data, such as rough receiver position and time or space vehicles’ (SV) ephemeris data, and on the broadcast navigation message structure. Some receivers, like the one used here for testing, embed an acquisition engine that can be activated on request and assures a low acquisition time; moreover, they implement ephemeris extension. In contrast, other consumer receiver manufacturers exploit a baseband-configurable processing unit, similar to the one implemented in the software receiver, with thousands of parallel correlators generating a multi-correlator output with configurable spacing, depending on the accuracy required. By selecting an appropriate number of correlators, depending on the available assistance data and on the accuracy required, the TTFF consequently varies.
We assessed the performance of the receiver under test for different C/N0, for hot, warm, and cold start, and for different constellation combinations, exploiting hardware-simulated GNSS data. Good results are achieved, especially when introducing Galileo signals.
Figure 4 reports the hot-start TTFF for different C/N0 values in the range 25–53 dB-Hz, computed using the receiver. The receiver, connected to a signal generator, is configured in dual-constellation mode (GPS and Galileo) and carries out 40 TTFF trials, with a random delay between 15 and 45 seconds. In a standard additive white Gaussian noise (AWGN) channel and in hot-start conditions, the results mainly depend on the acquisition strategy and on the receiver availability of correlators and acquisition engines. In an ideal case with open-sky conditions and variable C/N0, the introduction of a second constellation only slightly improves the TTFF performance; this result cannot be generalized since it mainly depends on the acquisition threshold of the receiver, which can change using signals of different constellations. In real-world conditions, the situation can vary.
Figure 4. Hot start TTFF for Galileo+GPS configuration versus C/N0 using the test receiver.
Cold Start. Secondly, we analyze TTFF differences due to the different structure of GPS and Galileo navigation messages. The I/NAV message of the Galileo E1 signal and the data broadcast by GPS L1 C/A signals contain data related to satellite clock, ephemeris, and GNSS time: parameters relevant to the position fix since they describe the position of the satellite in its orbit, its clock error, and the transmission time of the received message.
Table 1 shows some results in the particular case of cold start, with an ideal open-sky AWGN scenario. The TTFF is significantly lower when using Galileo satellites: while the mean TTFF when tracking only GPS satellites is equal to about 31.9 seconds (s), it decreases to 24.7 s when considering only Galileo satellites, and to 22.5 s in the case of dual constellation. Similarly, the minimum and maximum TTFF values are lower when tracking Galileo satellites. The 95 percent probability values confirm the theoretical expectations. Again, in the ideal case with open-sky conditions, the results with two constellations are quite similar to the performance of the signal with faster TTFF. However, in non-ideal conditions, use of multiple constellations represents a big advantage and underlines the importance of developing at least dual-constellation mass-market receivers.
Table 1. Comparison between TTFF (in seconds) in cold start for different constellation combinations.
Furthermore, it is interesting to analyze in more detail the case of a GPS and Galileo joint solution. GPS and Galileo system times are not synchronized, but differ by a small quantity, denoted as the GPS-Galileo Time Offset (GGTO). When computing a PVT solution with mixed signals, three solutions are possible: to estimate it as a fifth unknown, to read it from the navigation message, or to use pre-computed value. In the first case it is not necessary to rely on the information contained in the navigation message, eventually reducing the TTFF. However, five satellites are required to solve the five unknowns, and this is not always the case in urban scenarios or harsh environments, as will be proved below. On the contrary, in the second case, it is necessary to obtain the GGTO information from the navigation message, and since it appears only once every 30 seconds, in the worst case it is necessary to correctly demodulate 30 seconds of data. Both approaches show benefits and disadvantages, depending on the environment. The receiver under test exploits the second solution: in this case, it is possible to see an increase in the average TTFF when using a combination of GPS and Galileo, due to the demodulation of more sub-frames of the broadcast message.
Sensitivity: Performance in Harsh Environments
Harsh environment is the general term used to describe those scenarios in which open sky and ideal propagation conditions are not fulfilled. It can include urban canyons, where the presence of high buildings limits the SV visibility and introduces multipath; denied environments, where unintentional interference may create errors in the processing; or sites where shadowing of line-of-sight (LoS) path is present, for example due to trees, buildings, and tunnels. In these situations it is necessary to pay particular attention to the signal-processing stage; performance is in general reduced up to the case in which the receiver is not able to compute a fix.
A first attempt to model such an environment has been introduced in the 3GPP standard together with the definition of A-GNSS minimum performance requirements for user equipment supporting other A-GNSSs than GPS L1 C/A, or multiple A-GNSSs which may or may not include GPS L1 C/A. The standard test cases support up to three different constellations; in dual-constellation case it foresees three satellites in view for each constellation with a horizontal dilution of precision (HDOP) ranging from 1.4 to 2.1.
To perform TTFF and sensitivity tests applying the 3GPP standard test case, we configured a GNSS simulator scenario with the following characteristics, starting from the nominal constellation:
Six SVs: three GPS (with PRN 6,7, 21) and three Galileo (with code number 4, 11, 23);
HDOP in the range 1.4 – 2.1;
nominal power as per corresponding SIS-ICD;
user motion, with a heading direction towards 90° azimuth, at a constant speed of 5 kilometers/hour (km/h).
In addition to limiting the number of satellites, we introduced a narrowband multipath model. The multi-SV two-states land mobile satellite (LMS) model simulator generated fading time series representative of an urban environment. The model includes two states:
a good state, corresponding to LOS condition or light shadowing;
a bad state, corresponding to heavy shadowing/blockage.
Within each state, a Loo-distributed fading signal is assumed. It includes a slow fading component (lognormal fading) corresponding to varying shadowing conditions of the direct signal, and a fast fading component due to multipath effects. In particular, the last version of the two-state LMS simulator is able to generate different but correlated fading for each single SV, according to its elevation and azimuth angle with respect to the user position: the angular separation within satellites is crucial, since it affects the correlation of the received signals. This approach is based on a master–slave concept, where the state transitions of several slave satellites are modeled according to their correlation with one master satellite, while neglecting the correlation between the slave satellites. The nuisances generated are then imported in the simulator scenario, to timely control phase and amplitude of each simulator channel. Using this LMS scenario, the receiver’s performance in harsh environments has been then verified with acquisition (TTFF) and tracking tests.
The TTFF was estimated with about 50 tests, in hot, warm, and cold start, first using both GPS and Galileo satellites, and then using only one constellation. In the second case only the 2D fix is considered, since, according to the scenario described, at maximum three satellites are in view. Table 2 reports the results for the dual-constellation case: in hot start the average TTFF is about 8 s, and it increases to 36 s and 105 s respectively for the warm and cold cases. Clearly the results are much worse than in the case reported earlier of full open-sky AWGN conditions. In this scenario only six satellites are available at maximum; moreover, the presence of multipath and fading affects the results, and they exhibit a larger variance, because of the varying conditions of the scenario.
Table 2. TTFF (in seconds) exploiting GPS and Galileo constellations in harsh environments.
Table 3 shows similar results, but for the GPS-only case. In this case the receiver was configured to track only GPS satellites. The mean TTFF increases both in the hot and in the warm case, whereas in cold start it is not possible compute a 2D fix with only three satellites; the ambiguity of the solution cannot be solved if an approximate position solution is not available. It may seem unfair to compare a scenario with three satellites and one with six satellites. However, it can be assumed that this is representative of what happens in limited-visibility conditions, where a second constellation theoretically doubles the number of satellites in view.
Table 3. TTFF (in seconds) exploiting only GPS constellations in harsh environments.
The results confirm the benefits of dual-constellation mass-market receivers in harsh environments where the number of satellites in view can be very low. Making use of the full constellation of Galileo satellites will allow mass-market receivers to substantially increase performances in these scenarios.
Tracking.We carried out a 30-minute tracking test with both the receiver and the software receiver model. Both were able to acquire the six satellites and to track them, even with some losses of lock (LoLs) due to fading and multipath reflections. Figure 5 shows the number of satellites in tracking state in the receiver at every second, while Figure 6 shows the HDOP as computed by the receiver. When all six satellites are in tracking state, the HDOP lies in the range 1.4 – 2.1, as defined in the simulation scenario; on the contrary, as expected, in correspondence with a LoL it increases.
Figure 6. HDOP computed by the test receiver in the Multi-SV LMS simulation.
Figure 7 compares the signal power generated by the simulator and the power estimated by the receiver, in the case of GPS PRN 7 and Galileo code number 23. This proves the tracking capability of the receiver also for high sensitivity. To deal with low-power signals, the integration time is extended both for GPS and for Galileo, using the pilot tracking mode in the latter case.
Figure 7. C/N0 estimate computed by the receiver in harsh environments and compared with the signal power.
Figures 8 and 9 show respectively the position and the velocity solution. In the first case latitude, longitude, and altitude are plotted, while in the second case the receiver speed estimate in km/h is reported.
Figure 8. Test receiver position solution in LMS scenario.Figure 9. Test receiver velocity solution in LMS scenario.
In this framework it is possible to evaluate the advantages and disadvantages of using the broadcast GGTO when computing a mixed GPS and Galileo position. When the LMS channel conditions are good, all six SVs in view are in tracking state, as shown in Figure 5. However, when the fading becomes important, the number is reduced to only two satellites. If the receiver is designed to extract the GGTO from the navigation message, then a PVT solution is possible also when only four satellites are in tracking state, that is for 90 percent of the time in this specific case. On the contrary, if the GGTO has to be estimated, one more satellite is required, and this condition is satisfied only 57 percent of the time, strongly reducing the probability of having a fix. Nevertheless, estimating the GGTO requires the correct demodulation of the navigation message, and this is possible only if the signal is good enough for a sufficient time.
Figure 5. Number of satellites tracked by the test receiver in the Multi-SV LMS simulation.
Power-Saving Architectures
The final driver for mass-market receivers design is represented by power consumption. Particularly for chips suited for portable devices running on batteries, power drain represents one of the most important design criteria. To reduce at maximum the power consumption, chip manufacturers have adopted various solutions. Most are based on the concept that, contrarily to a classic GNSS receiver, a mass-market receiver is not required to constantly compute a PVT solution. In fact, most of the time, GNSS chipsets for consumer devices are only required to keep updated information on approximate time and position and to download clock corrections and ephemeris data with a proper time rate, depending on the navigation message type and the adopted extended ephemeris algorithm. Then, when asked, the receiver can quickly provide a position fix. By reducing the computational load of the device during waiting mode, power consumption is reduced proportionally.
To better understand advantages and disadvantages of power saving techniques, some of them have been studied and analyzed in detail. In particular, the algorithm implemented in the software receiver model is based on two different receiver states: an active state, in which all receiver parts are activated, as in a standard receiver, and a sleep state, where the receiver is not operating at all. In the sleep state, the GNSS RF module, GNSS baseband, and digital signal processor core are all switched off. By similarity to a square wave, these types of tracking algorithms are also called duty-cycle (DC) algorithms. Exploiting the software approach’s flexibility, we can test the effect of two important design parameters:
sleep period length;
minimum active period length.
Their setting is not trivial and depends on the channel conditions, on the signal strength, on the number of satellites in view, on the user dynamics, and finally on the required accuracy.
In the software receiver simulations performed, the active mode length is fixed to 64 ms: the receiver collects 16 correlation values with coherent integration time equal to 4 ms, to perform frequency estimation as described above. Then it switches to sleep state for 936 ms, until a real-time clock (RTC) wake-up initiates the next full-power state. In this way a fix is available at the rate of 1 s, as summarized in Figure 10. However, there are some situations where the receiver may stay in full-power mode, for example during the initialization phase, to collect important data from the navigation message, such as the ephemeris, and to perform RTC calibration.
Figure 10. Duty cycle tracking pattern in the software receiver simulations.
There are benefits of using this approach coupled to Galileo signals: the main impact is the usage of the pilot codes. Indeed, a longer integration time allows reducing the active period length, which most impacts the total power consumption, being usually performed at higher repetition rate.
Some simulations were carried out to assess the performance of DC algorithms in the software receiver. While in hardware implementations the direct benefit is the power computation, in a software implementation it is not possible to see such an improvement. The reduced power demand is translated into a shorter processing time for each single-processing channel. The DC approach can facilitate the implementation of a real-time or quasi-real-time software receiver.
The main drawback of using techniques based on DC tracking is the decrease of the rate of observables and PVT solution. However, this depends on the application; for some, a solution every second is more than enough.
Real-Signal Results
On March 12, 2013, for the first time the four Galileo IOV satellites were broadcasting a valid navigation message at the same time. From 9:02 CET, all the satellites were visible at ESTEC premises, and the first position fix of latitude, longitude, and altitude took place at the TEC Navigation Laboratory at ESTEC (ESA) in Noordwijk, the Netherlands. At the same time, we were able to acquire, track, and compute one of the first Galileo-only mobile navigation solutions, using the receiver under test. Thanks to its small size and portability, it was installed on a mobile test platform, embedded in ESA’s Telecommunications and Navigation Testbed vehicle. Using a network connection, we could follow, from the Navigation Lab, the real-time position of the van moving around ESTEC.
Figure 11 shows the van’s track, obtained by post processing NMEA data stored by the receiver evaluation board. The accuracy achieved in these tests met all the theoretical expectations, taking into account the limited infrastructure deployed so far. In addition, the results obtained with the receiver have to be considered preliminary, since its firmware supporting Galileo was in an initial test phase (for example, absence of a proper ionospheric model, E1B-only tracking).
Figure 11. Galileo-only mobile fix, computed on March 12, 2013.
Conclusions
Analysis of a receiver’s test results confirms the theoretical benefits of Galileo OS signals concerning TTFF and sensitivity. Future work will include the evolution of the software receiver model and a detailed analysis of power-saving tracking capabilities, with a comparison of duty-cycle tracking techniques in open loop and in closed loop.
Acknowledgments
This article reflects solely the authors’ views and by no means represents official European Space Agency or Galileo views. The article is based on a paper first presented at ION GNSS+ 2013. Research and test campaigns related to this work took place in the framework of the ESA Education PRESTIGE programme, thanks to the facilities provided by the ESA TEC-ETN section. The LMS multipath channel model was developed in the frame of the MiLADY project, funded by the ARTES5.1 Programme of the ESA Telecommunications and Integrated Applications Directorate.
Manufacturers
The tests described here used the STMicroelectronics Teseo II receiver chipset and a Spirent signal simulator.
Nicola Linty is a Ph.D. student in electronics and telecommunications at Politecnico di Torino. In 2013 he held an internship at the European Space Research and Technology Centre of ESA.
Paolo Crosta is a radio navigation system engineer at the ESA TEC Directorate where he provides support to the EGNOS and Galileo programs. He received a MSc degree in telecommunications engineering from the University of Pisa.
Philip G. Mattos received an external Ph.D. on his GPS work from Bristol University. He leads the STMicroelectronics team on L1C and BeiDou implementation, and the creation of totally generic hardware that can handle even future unknown systems.
Fabio Pisoni has been with the GNSS System Team at STMicroelectronics since 2009. He received a master’s degree in electronics from Politecnico di Milano, Italy.
The R&S SMBV100A vector signal generator can generate Galileo, GPS, and GLONASS signals for up to 24 satellites in real time. With the SMBV-K107 option, the simulator covers the BeiDou standard as well.
The R&S SMBV-K101 option allows developers in the automotive and wireless communications industries to test GNSS receivers for specific effects such as obscuration and multipath propagation. If the GNSS receiver of a navigation instrument or smartphone is located inside a vehicle, testing must also take into account the obscuring effect of the vehicle’s metal body. The R&S SMBV-K102 option can simulate this obscuration and, if required, the additional antenna pattern.
In addition to test scenarios for A-GPS, smartphone developers have the Assisted Galileo (R&S SMBV-K67) and Assisted GLONASS (R&S SMBV-K95) options at their disposal.
