Trade wars may be THE only serious limiting factor
The GNSS chip market worldwide is projected to grow by $2.7 billion, guided by a compounded growth of 8%, to 2025, according to ResearchandMarkets. Other market reports cite “huge growth” and “strong development” in GNSS-related markets such as simulators, aviation and defense. We can count ourselves lucky — or remarkably prescient — to be part of such a robust industry, in such uncertain times.
The world conquest by smartphones, smart cities and the internet of things (IoT) will strongly support this market growth. Also on the horizon is the rising tide of GPS-enabled vehicles, putting automotive telematics on the road to assisted-driver and ultimately autonomous driving.
M&A. Meanwhile, the fast pace of mergers and acquisitions among manufacturers and integrators will strengthen the GNSS economy and propel it even higher. Such interactivity will bring higher revenue shares to key players as well as support overall profitability increases to come.
Accurate monitoring of operations and assets; the astonishing rise of drones to active roles in many industries; and the constant innovation and imagination churning out new products, solutions and augmented services — all will consolidate the strength of our remarkable economy. The much-heralded arrivals of BeiDou and Galileo fully upon the scene will only make the immediate future stronger for our industry.
Chart: GPS World
PNT Broadly. Where GPS, GNSS, and multi-GNSS go, they carry other positioning technologies along on their coat tails: inertial, signals of opportunity, Wi-Fi, ultra-wideband and more. The growing pie is certainly big enough for all to get a large share.
That’s not to say there are no barriers to growth, no clouds on the horizon. Licensing, laws and regulations will, as ever, constrict growth. This is not always a bad thing. Controlled growth and wise use benefit us all, and prevent runaway bubbles that can burst for lack of proper internal support.
Mapping. Meanwhile, a host of well-established businesses and nascent enterprises exploit the increased interest in location-based information as an enabler for many consumer, organizational and governmental services. This means that mapping and all manner of technologies associated with it — laser, lidar, infrared and more — may grow at even faster rates.
A brave new world awaits. Once GNSS is integrated with artificial intelligence, there’s no telling where we’re headed.
Of the many uncertainties across the globe, economic warfare poses a greater risk to GNSS than does military conflict. The latter, cynically enough, will actually benefit the industry in the short run, though its effect may chill in the long run.
Chart: GPS World
Trade. One of the biggest questions confronting the industry now is whether the trade and tariff war between the U.S. and China will continue, and what effect it will have. Experts disagree widely on both questions, though almost all of them, except the leaders who are supposed to listen to them, agree that it’s generally a bad thing.
As was stated in these pages at this time last year, if business confidence falls as a result, global output could also drop.
Opportunities Outweigh Obstacles
Industry leaders confront spectrum issues, jamming
In contrast to the rosy forecast on the previous page, serious issues confront the GNSS market. None of them are more serious, thornier or difficult to resolve (despite the many solutions offered) than spoofing and jamming.
Like a tragic hero, GNSS carries a potentially fatal weakness within its strength. To be ubiquitous and highly precise, the signals come from space. Coming from space, they are weak and susceptible to malicious meddling.
Other political and technological obstacles put pressure on the GNSS industry, and therefore upon the whole PNT industry. GNSS always will be the backbone, the center core holding together various adjunct positioning, navigation and timing technologies.
These issues, following closely on the heels of spoofing and jamming, include but are not limited to: spectrum competition and spectrum management; cybersecurity; privacy; net neutrality; national security export controls; product liability; and failure, however temporary, of GNSS systems.
We’ve seen this last most recently with Galileo, but all the GNSS have suffered such setbacks, and surely will again. The nature of the response to each occurrence is the most critical factor.
Keep on the Sunny Side. However, the opportunities far outweigh the obstacles. The greatest opportunities always arise from the greatest asset that the industry possesses: intellectual capital.
Many of the opportunities are cited on the previous page. While high precision will continue to lead the innovation charge and provide the highest profit margins, the smartphone and the automobile will increasingly take up the MVP (most valuable positioner) role within the industry.
Market Intelligence. All these factors make unprecedented demands on management attention and agility. Executives need good market intelligence to keep abreast and ahead of fast-developing research and development trends, market shifts, developments in neighboring or competing technologies, and protectionist tariffs and import/export controls.
Insight provided by all regions, sectors and job titles
This year’s State of the GNSS Industry Survey provides insight from around the globe.
Just over half our respondents work for companies or organizations headquartered in North America; 15% are from Asia-based operations; roughly 10% each for enterprises in Europe and Latin America; slightly less for the Pacific region; and the rest of the replies scattered across Africa, the Middle East and Russia. Truly an international sampling!
Chart: GPS WorldChart: GPS WorldChart: GPS WorldChart: GPS World
Demographics. For job titles, we drew in-depth data from:
owner/president/CEO, 21%
engineer, 20%
general, product or program manager, 19%
other, mostly surveyors or GIS analysts, 18%
researcher, 10%
vice president, CTO, COO, CFO or similar, 6%
sales and marketing, 5%
Sector. The intelligence in the following pages accumulated from these industry verticals:
survey and high precision, 29%
defense, security, government, 19%
mapping, data acquisition/processing, GIS, 14%
satellites, signals and simulation, 9%
machine control, precision agriculture, or transportation (non-autonomous), 6%
Portos Team paired with the Ninja. (Photo: iP-Solutions)
Japan-based iP-Solutions has introduced Portos Team, a new GNSS RF signal record-and-playback system.
The Portos Team can record and play back — or simulate —multi-frequency, multi-system GNSS signals when paired with the company’s Replicator. It can do the same for CRPA signals when paired with the Ninja (see photo).
The Portos itself can also operate as multi-frequency or CRPA front-end for a GNSS software receiver.
The high-end Ninja simulator allows for multi-antenna controlled radiation pattern antenna (CRPA) and local-area augmentation system (LAAS) simulation, the company said.
The 24-channel Replicator — developed in collaboration with the Japan Aerospace Exploration Agency (JAXA) — provides real-time generation of GNSS signals, recording and playback of dual-frequency GNSS RF signals, and GNSS RF signal analysis with JAXA COSMODE ionospheric scintillation monitor.
Racelogic Ltd. has released the latest update to its SatGen GNSS simulation software for PC, which now incorporates Galileo RF simulation.
Designed to create a GNSS RF I&Q or IF data file based on a user-generated trajectory file, the updated software can now accurately simulate the European Galileo GNSS satellite constellation alongside existing GPS, GLONASS and BeiDou RF signal generation.
The full range of Galileo frequencies that SatGen can simulate are Galileo E1 B/C, E5a, E5b and E6 B/C (see below for details).
SatGen 3.11.39 Galileo simulated RF frequencies
Galileo E1 B/C. Transmitted by all Galileo satellites on the E1 (1575.42 MHz) frequency, same as GPS L1. Standard precision Open Service signal consisting of Data component B and Pilot component C.
Galileo E5a. Transmitted by all Galileo satellites on the E5a (1176.45 MHz) frequency, same as GPS L5. Open Service signal consisting of Data component I with the F/NAV navigation message and Pilot component Q. Intended to be used together with E1 B/C to improve accuracy.
Galileo E5b. Transmitted by all Galileo satellites on the E5b (1207.14 MHz) frequency, same as BeiDou B2. Open Service signal consisting of Data component I with the I/NAV navigation message and Pilot component Q. Intended to be used together with E1 B/C to improve accuracy.
Galileo E6 B/C. Transmitted by all Galileo satellites on the E6 (1278.75 MHz) frequency. High accuracy Commercial Service signal consisting of Data component B and Pilot component C. Because the content of the C/NAV navigation message is encrypted, SatGen transmits a dummy navigation message, which should be accepted by all receivers.
“Given the vast improvements in navigation and timing that Galileo has brought to its global users, we extremely excited to be releasing a version of SatGen that allows engineers to generate Galileo-specific scenarios for their test procedures,” said Mark Sampson, LabSat product manager.
Other changes to the software include various user interface tweaks, performance optimization and fixes.
For more information on SatGen, contact Katie Harland or call Racelogic LabSat at +44 1280 823 803.
Spirent Federal Systems, a provider of GPS/GNSS test equipment, announced that Col. (retired) Bernard Gruber, former program director of what is now the U.S. Air Force GPS Directorate, has joined the company’s board of directors as government security committee chairman. Also joining as the chairman of the board is Robert Lollini.
Spirent Federal President/CEO Ellen Hall stated, “We are happy to have retired Col. Gruber and Bob Lollini joining our dynamic company. We are leading the industry in innovation and quality products for the U.S. government and these two new leaders will help us continue that momentum.”
Col. Bernie Gruber in 2012. (Photo: U.S. Air Force)
Bernard Gruber brings to the position the experience gained from a long and distinguished career in the government and military sector. Mr. Gruber has held several positions in important commands focused on navigation in space, including serving as the chief of Space and Global Integrated Intelligence at the Pentagon from 2009-2010, and director of the Global Positioning System (GPS) at the Los Angeles Air Force Base from 2010-2013. He is currently the director of Precision Guidance and Advanced Programs, Armament Systems at Northrop Grumman.
Robert Lollini is currently the chief executive officer and president of BioFire Defense LLC, a subsidiary and proxy company of bioMerieux. Lollini contributes to the board his broad understanding of strategic financial and executive management.
Spirent Federal Systems was formed in July 2001 by Spirent Communications as a wholly owned subsidiary and U.S. proxy company. Spirent Federal markets and sells Spirent Communications’ GNSS products in North America. The company also provides value-added features and ongoing customer support. Spirent Federal Systems is headquartered in Pleasant Grove, Utah, with support and sales offices throughout the U.S.
Testing the antenna performance of GNSS signals such as GPS, GLONASS, Beidou, Galileo and Metropolitan Beacon Systems (MBS) is key to location accuracy performance of a mobile device.
To address the testing need for A-GNSS services, Rohde & Schwarz and Bluetest are partnering in creating test concepts for over-the-air (OTA) antenna measurements.
The CMW500 wideband radio communication tester. (Photo: Rohde & Schwarz)
The two companies integrate the R&S LBS Server, a software component running on the R&S CMW500 wideband radio communication tester, and the Bluetest OTA test solution for A-GNSS systems based on Bluetest’s RTS65 reverberation chamber and Bluetest’s Flow measurement software.
In the test setup, the R&S LBS Server controls the Rohde & Schwarz base-station simulator R&S CMW500 for LTE, WCDMA and GSM, and uses the R&S SMBV100B vector signal generator for simulation of GNSS and MBS signals.
A simple and straightforward upgrade of the setup for 5G will be available soon, making sure that investments are protected and most relevant standards can be tested with the same system.
The R&S LBS Server is an essential part of the R&S TS8991 OTA Performance Test System. This cooperation between Rohde & Schwarz and Bluetest marks the first time that the R&S LBS Server, used here as a software tool on R&S CMW500, is available also for third parties.
“We are delighted to collaborate with Bluetest to contribute with our test and measurement expertise to OTA 4G/3G/GSM and GNSS technology development,” said Alexander Pabst, vice president, Systems and Projects at Rohde & Schwarz. “With a strong global footprint for location based services LBS and close cooperation with partners, Rohde & Schwarz is committed to accompanying the evolution path from OTA testing for GPS, GLONASS, BeiDou and Galileo with innovative test and measurement solutions.”
“The addition of A-GNSS measurements means that the full range of wireless technology in a modern cellular device can be verified with just one test solution,” said Robert Rehammar, Bluetest CTO. “Bluetest has enjoyed the close cooperation with Rohde & Schwarz on this project, leading to a very strong joint solution and customer offering.”
A GPS/inertial trajectory data simulation podium can generate simulation data sets for all levels of GPS/INS integration. Here it verifies the operation and performance of a new ultra-tight GPS/INS integrated system, adaptable for both software and conventional hardware receivers.
Navigation systems for land vehicles, embedded in passenger cars, ambulances, police cars, fire trucks and others, provide reasonable accuracy in open-sky environments, but under conditions such as underpasses and tunnels GPS satellite signals cannot be readily tracked since they are not consistently available or have low signal power. One major factor that directly impacts the effectiveness of receivers in terms of complexity and speed is receiver architecture.
Scalar (conventional) signal tracking architectures process each satellite signal individually: pseudoranges and pseudorange rate measurements are produced separately and only combined in the navigation filter to generate the required solution. Hence, no information exchange happens between the different tracking channels.
On the contrary, vector tracking systems combine all the channels in one system along with the navigation filter to produce pseudoranges, pseudorange rates and the navigation solution all at the same time. Figure 1 shows the general architecture of a vector tracking system. Vector-tracking architectures have proven themselves able to provide better performance over scalar tracking systems in challenging environments where most satellite signals are received at low signal-to-noise ratios (SNR).
Figure 1. General view of the vector-based signal tracking system. (Image: Authors)
Any information available about the satellite constellation and user position and dynamics can be used to predict the received signals. Therefore, the best estimation we have for the receiver position and dynamics makes the vector tracking loops more robust. One approach to reduce or perhaps remove the receiver dynamic stress in the signal tracking loops is to provide external aiding information.
Several sensor types have been augmented with GPS to improve navigation system accuracy and reliability. The most common systems that have been widely augmented with GPS are inertial sensor systems (INS). Because an INS system can provide a continuous solution at a high data rate, it is virtually a twin to the GPS with respect to its widespread use in navigation applications.
Using the solution obtained from INS, one can estimate a line-of-sight acceleration that can be integrated to obtain a line-of-sight velocity. Car odometers also provide reasonably accurate measurements of the vehicle speed. Incorporating this velocity (from INS or other aiding sources) into tracking-loop computations helps the tracking loop to maintain tracking at a lower bandwidth even when high dynamics are experienced at the receiver. When the aiding source to the GPS signal tracking loops is an INS, the system is known as ultra-tight GPS/INS integration. Figure 2 shows a general block diagram of an ultra-tightly coupled GPS/INS integration system.
The ultra-tight GPS/INS integrated system enhances a GPS receiver’s tracking ability in challenging environments and consequently improves navigation availability.
Loose. The loosely coupled integration mode is easier to implement since the inertial and GPS navigation solutions are generated independently before being weighted together in a separate navigation filter. The advantages of this coupling strategy are that the INS errors are bounded by the GPS updates, the INS can be used to bridge GPS updates, and the GPS can be used to help calibrate the deterministic parts of the inertial errors instantly. The main drawback of this strategy, however, is that it requires at least four satellites in view which cannot always be guaranteed because of signal interruption due to many factors such as signal blockage by trees or tall buildings.
Tight. The tightly coupled integration mode combines both systems into a single navigation filter. The major limitation of visibility of at least four satellites is removed since this integration mode can provide a GPS update even if fewer than four satellites are visible. The tightly coupled architecture also overcomes the problem of correlated measurements that arises due to cascaded Kalman filtering in the loosely coupled approach. However, these advantages come with the penalty of increased system complexity.
Ultra-tight. In the ultra-tightly coupled integration approach, the raw measurements come from one step further towards the front end of a GPS receiver, in the form of I (in-phase) and Q ( quadrature ) signal samples. These I and Q measurements are integrated with the position, velocity and attitude of the INS in a complementary filter. The integration of INS-derived Doppler feedback to the carrier tracking loops provides a vital benefit to this system; the INS Doppler aiding removes the vehicle Doppler from the GPS signal. Hence, it results in a significant reduction in the carrier tracking loop bandwidth. In addition, due to lower bandwidths, the accuracy of the raw measurements is further increased.
The proposed method uses a variant of the Kalman filter as the core of the navigation processor coupled with the inertial sensor’s input in a reduced inertial sensor system (RISS) configuration and car speed odometer; see Figure 3. Additionally, the data sets used in this work are generated using a newly composed GPS/INS trajectory data simulation platform.
Figure 3. Reduced inertial sensor system (RISS). (Image: Authors)
Secondly, it demonstrates a novel GPS/INS trajectory data simulation podium. This combined simulation system can produce simulation data sets for all levels of GPS/INS integration and is used to verify the operation and performance of the ultra-tight GPS/INS integrated system.
SYSTEM ARCHITECTURE AND IMPLEMENTATION
The goal of signal tracking loops is to monitor changes in the main signal parameters, namely, code phase and carrier frequency, to keep the locally generated signal aligned with the received signal. Successful tracking of these variables will provide good estimations of the parameters that are required for the navigation filter to function correctly. Errors in the code phase and carrier frequency are usually represented as:
(1)
(2)
where and are the measured and estimated code phases, respectively. and are the measured and estimated carrier Doppler frequencies, respectively. These estimated errors at the signal tracking stage are directly linked to the errors in the states at the navigation filter.
Each tracking channel provides its own measurements based on a discriminator’s output. All the measurements are then processed together in the navigation filter and feedback is provided to each channel based on the obtained navigation solution results. The filter will process the error signals received from the discriminators in the form of code phase error and frequency error . Thus, the measurements of the filter will be pseudorange errors and pseudorange rate errors.
(3)
(4)
Where fcode is the code frequency = 1.023 x 106 Hz, fcarrier is the nominal L1 frequency = 1575.42 MHz, and η represents the measurement noise vector.
The computations of the navigation solution start with a mechanization process where we first calculate pitch, roll and azimuth angles. Knowing the Azimuth and pitch angles, vehicle forward velocity can be projected into East, North and Up velocities. The East and North velocities are transformed into geodetic coordinates and then integrated over the sample interval to obtain positions in latitude and longitude. The vertical component of velocity is integrated to obtain altitude. At this stage, we run the Kalman navigation filter through its two-step known cycle, prediction and update, incorporating any available measurements to estimate the receivers’ new position and velocity. Then, the estimated pseudoranges and pseudorange rates are calculated. Finally, the computed code and carrier frequencies are fed back to control the code and carrier oscillator inputs to align the locally generated signal with the incoming signal.
COMBINED SIMULATION SYSTEM
In our work, we combined two existing INS and GNSS simulators to build a comprehensive simulation tool that can produce a limitless number of data sets of repeated trajectories under entirely controlled circumstances. Moreover, these data sets can be used for any level of GPS/INS integration system validation. The system is also used to verify the performance of the above proposed ultra-tight GPS/INS integration system architecture.
For the GPS data, a satellite navigation simulation signal generator was used to build and generate the desired trajectory. The selected model has the ability to provide dynamic capacity in Doppler and signal power levels as well as adequate channels to simulate line-of-sight and multipath satellite signals. The unit is driven by a software package that comes in different versions; the most powerful version is used in this research to drive the simulation hardware system to generate the output radio frequency (RF) signal.
A receiver front-end then generates the discretized data stream in the form of in-phase (I) and quadrature-phase (Q) signals. The unit is a rugged dual-frequency L1/L2 front-end intended mainly for software receiver and interference detection systems. The unit is capable of logging L1/L2 data at bandwidths of 2.5 MHz, 5.0 MHz, 10 MHz and 20 MHz with data quantization varying from 1 bit to 8 bits.
For the INS data sets, the INS simulator, developed by the Mobile Multi-sensor Group at the University of Calgary, is used for simulating inertial measurement unit (IMU) raw data. The INS simulator can virtually generate the raw data measurements of any grade of IMUs such as navigation, tactical and consumer-grade systems. A wide number of sensor errors can be simulated using this software such as bias instability, random walk, scale factor, errors due to thermal drift and g-sensitivity and so on. While the simulator can generate raw IMU measurements using user-defined vehicle motion and dynamics, such as static scenarios, straight line, constant velocities, accelerations, turns and bumpy roads, and it can also accept externally injected vehicle dynamics from real trajectory data.
Figure 4 shows a high-level diagram of the trajectory data flow from the two arms of the synthesized simulator. Several conversion code scripts were written to convert raw data into the implementation platform workspace format. Both data sets were then merged through the implemented algorithm to provide the navigation solution.
Figure 4. Data simulation tool flow diagram. (Image: Authors)
Step 1 of Simulation Process. The trajectory design, Figure 5, outlines the general aspects of the process. Among these are the type of platform to be simulated, for example. land vehicles, ships, aircraft and so on; the satellite constellation, typically GPS, Galileo or GLONASS; the environment, whether rural, suburban or urban; and error sources, including ionospheric and tropospheric effects. All of this is done using the simulator’s software.
Figure 5. Trajectory data flow Step 1. (Image: Authors)
Step 2. This incorporates the implementation of the data stream that is fed into the signal generator hardware, which transforms this into an RF signal (Figure 6). Concurrently, the reference trajectory data is logged on the same computer that hosts the simulation software. The I and Q branches are recorded, simultaneously with the reference trajectory, on a GNSS receiver front-end.
Figure 6. Trajectory data flow Step 2. (Image: Authors)
Step 3. Finally, the inertial data is simulated. First, the INS simulator is configured according to the desired simulation parameters. Among these are the sensor data rate, grade (or quality) of the selected sensor(s), and some initialization quantities that are obtained from the output of the GNSS signal simulator. Once the configuration process is complete, data extracted from the reference trajectory is converted into a format appropriate to the INS simulator, and the inertial data simulation is performed. At this stage, data from both the GNSS side and INS side can be converted into a format suitable for use by the integrated INS/GNSS system (see Figure 7).
Figure 7. Data flow, Step 3. (Image: Authors)
EXPERIMENTAL WORK
Using the complete simulation system, several simulation data sets are used to verify the performance of the proposed algorithm in semi real-life scenarios. Each time a chosen scenario is run on the Spirent GNSS simulator, the software data is applied to the Spirent hardware to generate the RF signal, which is then applied to the input of the front-end unit to provide the corresponding I and Q signal streams. Meanwhile, the trajectory data is logged from the simulator to be used as a reference and then fed to the INS simulator to generate the corresponding raw IMU data. Finally, the I and Q and raw IMU data are combined (when the ultra-tight solution is used) in a software receiver code to extract the ultimate positioning solution. For scalar and vector-based signal tracking, only GPS data is used. One sample trajectory that simulates a land vehicle driving at low speed is selected to show results of the proposed method.
Table 1 shows initialization of the key parameters during the simulation period. A GPS-only satellite constellation is used. We also limited the maximum number of simulated satellites to seven.
RESULTS
The reference solution used to evaluate the proposed method and combined simulation system is the pure data sets extracted from the Spirent GNSS simulator. The figures below show results of 80 seconds of data processing. At around seven seconds of the period, a 43-dB signal drop was applied for 8 seconds on channel number 1, which is assigned to track PRN number 06. A similar signal drop is partially overlapped with this, but was applied for only 5 seconds on channel number 3, which is dedicated to track PRN number 21. The following abbreviations are used in the figures: ST for scalar tracking, VT for vector tracking, and UT for ultra-tight GPS/INS integration system.
Figure 8 and Figure 9 show the carrier frequency for PRN 06 and PRN 21. Large frequency errors (greater than 100 Hz) are noticeable in the scalar tracking system. The vector tracking system, however, was much less affected, showing more resistance to the drop in signal-to-noise ratio. The ultra-tight GPS/INS integration system was nearly unaffected and maintained a very accurate carrier frequency estimation throughout the simulated trajectory.
Figure 8. Estimated carrier frequency for PRN #6. (Image: Authors)Figure 9. Estimated carrier frequency for PRN #21. (Image: Authors)
The trend of the position errors is plotted in Figures 10, 11 and 12. The maximum position error was around 15 meters in the case of vector tracking, whereas the maximum position error from the ultra-tight system was below 4 meters in the worst case.
Figure 10. Position X error. (Image: Authors)Figure 11. Position Y error. (Image: Authors)Figure 12. Position Z error. (Image: Authors)
Velocity errors are depicted in Figures 13, 14 and 15. Velocity errors for the vector tracking system reached about 2 meters per second during the low signal-to-noise ratio period. However, they were only small fractions of a meter per second for the ultra-tight GPS/INS integration system.
Figure 13. Velocity X error. (Image: Authors)Figure 14. Velocity Y error. (Image: Authors)Figure 15. Velocity Z error. (Image: Authors)
CONCLUSIONS
This article shows the performance of a newly proposed ultra-tight GPS/INS integrated system using an RISS that is intended to enhance GPS receivers’ tracking ability in challenging environments, thus improving navigation availability. Additionally, we present a freshly combined GPS/INS trajectory data simulator that can be used to generate simulation data sets for all levels of GPS/INS integration. The two components of the simulator are demonstrated to be perfectly linked. Performance of the algorithm was tested using several trajectories, and the algorithm demonstrated durability against harsh signal degradation. Acceptable position and velocity errors were achieved. Expected future improvements to the algorithm aim to employ longer integration time, and the performance of different grades of IMUs are to be simulated.
ACKNOWLEDGMENT
This work described in this article was first presented at the ION GNSS+ 2018 conference in Miami, Florida.
MANUFACTURERS
The Spirent GSS6700 Satellite Navigation Simulation Signal Generator was used in these tests, with SimGen software. The NovAtel FireHose front-end generated the discretized data stream.
MALEK KARAIM is a Ph.D. candidate at the Department of Electrical and Computer Engineering, Queen’s University, Canada. He is working within the Navigation and Instrumentation Research (NavINST) Group at Queens’ University/Royal Military College of Canada.
MOHAMED YOUSSEF received his Ph.D. degree from the Department of Geomatics Engineering and the Department of Electrical and Computer Engineering, University of Calgary, Alberta, Canada. He leads GNSS R&D activities at Sony North America.
ABOELMAGD NOURELDIN is a cross-appointment associate professor at the departments of electrical and computer engineering in Queen’s University and the Royal Military College (RMC) of Canada. He is the director of the Navigation and Instrumentation Research Laboratory at RMC.
MicroPilot is working with Simlat to develop a pan, tilt and zoom payload simulation tool to help improve the camera-centric parts of MicroPilot’s autopilot software.
Simlat is a provider of training systems for UAVs, enabling training on any platform with any payload for any mission. The tool Simlat has developed emulates a camera payload on a UAV, including simulated video, when set up with an “iron bird.”
This allows more testing to be performed on the ground, and potential problems with the payload worked out before flight testing begins.
“Flight testing is time consuming and expensive and simulation is an essential tool that reduces the amount of flight testing necessary to bring a drone to market,” said Howard Loewen, president of MicroPilot. “We are pleased to be working with Simlat to add this capability to our software development process.
“MicroPilot is always looking for useful tools and features to integrate with our products in order to help deliver more capable and reliable products to our customers. This camera payload emulator is just one of many third-party tools we have incorporated into our testing and development and yet another way MicroPilot has shown its dedication to product quality and performance.”
MicroPilot is an ISO 9001 autopilot manufacturer to bring to market an ISO 9001 sub-30-gram autopilot, triple redundant autopilot, and full-function general-purpose autopilot. MicroPilot offers a family of lightweight UAV autopilots that can fly fixed-wing, transitional, helicopter and multirotor UAVs.
In mid-2017, Talen-X and Skydel engineers began to conceptualize a GNSS simulation system emanating from their BroadSim platform for the purpose of fortifying anechoic chambers.
Over the next six months, Talen-X and Skydel designed, built, tested and delivered an anechoic chamber simulator capable of simultaneously generating multi-GNSS jamming and spoofing signals.
BroadSim Anechoic can be used to support a wide variety of operational tests.
“Our new Anechoic Chamber solution will radically change the way in which mission critical platforms and systems are tested because we are enabling our customers to create real-world threats,” said Talen-X Chief Technology Officer Tim Erbes said. “Not only will BroadSim Anechoic be able to emulate real-world threat scenarios, it will be easier than ever before to create and simulate these environments.”
BroadSim Anechoic is used to test GNSS spoofing and jamming in an anechoic chamber. The BroadSim Controller is at the heart of the system running Skydel’s SDX software suite. Using SDX, users can create advanced scenarios that include both jamming and spoofing signals.
The 16 software-defined radios (SDRs) each with dual transmit ports (32 total outputs) can be configured to output GNSS or jamming signals, giving users flexibility to run test after test. The transmit chains include the hardware to power 16 dual-frequency antennas. The included GNSS receivers allow users to monitor the environment inside the chamber, providing confidence that tests are running correctly.
The BroadSim Anechoic can also be used in controlled radiation pattern antenna (CRPA) testing. Many ground-, airborne- and water-based platforms are transitioning to using CRPAs because of their added jamming resiliency and significant tracking advantages in degraded environments.
Validation and real-world testing is critical to understanding and characterizing the mitigation these antennas can add in highly degraded areas. By using BroadSim Anechoic, users have the ability to create representative jammers with real-world characteristics (modulations, frequencies, angles, power levels, etc).
“Skydel developed an innovative approach for time offset calibration between multiple transmitting antenna using a COTS Software-Defined Radio (SDR),” said Skydel Solutions Chief Technology Officer, Iurie Ilie. “This approach allows for very precise measurements and adjustments (better than 100ps) to be done automatically before simulation start. At the same time, transmitting signal power is automatically adjusted to keep the power offset at receiving antenna better than 0.1dB.”
BroadSim Anechoic takes advantage of state-of-the-art software defined radios (SDR) for RF up-converting while signal IQ generation is done using high performance commercial-off-the-shelf (COTS) graphics-processing units (GPU). The ability to generate the IQ data in software (using the GPU) as opposed to hardware (FPGA) significantly reduces the cost while maximizing capability, value, and time to market.
BroadSim Anechoic has the capability of powering up to 16-dual frequency antennas requiring 32 RF transmit outputs. The architecture used for this system required the ability to receive signals in a manner such that precise processing could be done on the receive signal.
The SDR selected for this application has one receiver channel for every transmit channel giving BroadSim Anechoic 32 RF receive ports. Innovative software techniques have been developed enabling the accurate time and power calibration for each antenna transmit chain using the SDR receive ports.
Jackson Labs Technologies Inc. (JLT) is offering the CLAW GPS/GNSS simulator. Designed with small size, weight and power (SWAP), the CLAW is only slightly larger than a standard deck of cards.
CLAW targets applications that require small, low-power and low-cost GNSS synthesis with repeatable and highly accurate GNSS RF signals such as production testing of GNSS receivers, simulating GNSS anomalies such as leap-second events, 1023 GPS Week roll-overs, simulated operation in inaccessible locations around the world, real-time transcoding of different GNSS systems, and testing using dynamically user-configured RF signal levels.
With nanosecond-accurate encoding, CLAW is particularly suited to allow easy stress-testing of GPSDO frequency and timing reference products such as JLT’s GNSDOs under various different mission scenarios, the company said.
The CLAW GNSS simulator is a no-frills solution that contains real-time processing hardware to simulate GPS constellations without the need to connect any external equipment other than a USB power source or power supply.
Providing a real-time computed RF output signal rather than an offline file-playback differentiates CLAW from competitive solutions that are only capable of recording and playback operation in non-real-time, or require offline computation of data files using external computers that are played back on the simulation device.
CLAW is a completely self-contained, ruggedized, miniature, real-time hardware GPS simulator.
Navigation coordinates and 1PPS timing pulses can be provided in real-time through the NMEA and SCPI compatible USB interface or via the built-in RS-232 interface, and are encoded in the CLAW into RF GPS signals in real-time with nanosecond-level accuracy and minimal delay.
Position, velocity and timing (PVT) information may be provided as a simple NMEA stream from an external source such as an inertial navigation system (INS), Galileo/GLONASS/BeiDou/SAASM GNSS receiver, and CLAW will encode this PVT data into standard L1 C/A GPS RF signals in real-time with minimal phase/position shifts. This allows real-time GNSS transcoding of any other GNSS standard simply by connecting an external GNSS receiver, INS system or PVT source to the RS-232 inputs of the CLAW, allowing retrofit of existing legacy equipment with the latest GNSS systems.
CLAW includes glueless drivers for Rockwell Collins Remote Secure Receiver (RSR Puck) among others, allowing transcoding of assured, secure L2 P(Y) code into legacy L1 C/A code in real time to retrofit commercial receivers with military P(Y) capability. CLAW also allows user-entry of ephemeris and almanac information, providing a means to simulate any past or future GPS constellation and time/date event, the company added.
CLAW was designed with a particular emphasis to encoding the optional externally-provided 1PPS GPS system time with nanosecond-level accuracy targets, allowing accuracy testing of GPS timing and frequency devices on top of simply providing a positioning/velocity reference. CLAW initially will support GPS L1 C/A code encoding with up to 12 satellites, and later versions will support additional GNSS systems such as L2 GPS, GLONASS, BeiDou and Galileo.
A comprehensive cost-free optional user application for Windows will be offered that allows control and monitoring of the unit, creation of simulation scenarios using Google Earth and manual waypoint entry, among other options. The unit also can be controlled via simple serial terminal commands, or various other available public-domain freeware programs.
Once position information is stored in the units’ NVRAM, the unit will generate GPS RF constellations within seconds upon power-up and thus does not require any user interaction other than plugging in the power supply.
CLAW contains a highly accurate and stable internal 10-MHz reference oscillator that may optionally be synchronized by an external 1PPS reference, 10-MHz reference, or both. CLAW supports a user-selectable RF signal attenuation range of 63 dB in 0.5-dB steps, allowing a wide range of RF signal levels to be generated with high accuracy and power-level resolution. Antenna DC power consumption also can be controlled via software command.
CLAW can be powered by its USB interface, or by a 6.5V to 28V DC power feed, and consumes less than 1.7W allowing extended operation of 24 hours or more from low-cost ubiquitous USB consumer battery packs.
“Prepare for Tomorrow: Find Vulnerabilities Today” was the title of our wide-ranging webinar in July that focused on GNSS signal simulation for jamming and spoofing scenarios. We did not have time to address all the questions posed by the audience, so we return to them here.
Q: While testing receivers, realistic scenarios for jamming and spoofing are very important. What is the typical approach to set the number of interference sources, their type and main signal parameters?
Two different approaches are common, those involving the use of an anechoic chamber and those which are lab-based. Each approach has its limitations and merits. Each approach must address the number of significant interferers, their signal powers and the waveforms of the interference signals. Each must also consider the geometric arrangement of these interferers relative to the antenna under test and relative to the simulated constellations under test.
Changes in signal phase, signal Doppler and signal power are as important for the interference signals as they for the wanted GNSS signals. These changes are caused by the simulated motion of the vehicle and potentially the motion of the interferers. These changes should also include the impact of terrain surrounding the vehicle and the interferers, and also the gain and phase patterns of the receive antenna on the vehicle and the transmit antennas on the interferers. Some interferers might be discounted from the significant set due to their signals being masked from the vehicle by the terrain or antenna patterns or by them being too far from the vehicle to have an impact. These interference signals may become significant as the scenario progresses due to vehicle or interferer motion.
Simulator graphical user interface. (Image: Spirent Federal Systems)
Q: In GNSS navigation systems for commercial applications, what emphasis of design effort should be on anti-jamming/anti-spoofing over improving the navigation accuracy?
Commercial applications is a broad area, so it will depend on the particular application as to whether it needs more accuracy or more resiliency against AJ/AS, but in general, the accuracy of GNSS is fairly mature. Standard GNSS offers accuracies on the order of ~1 meter. Centimeter accuracy can be achieved with differential or real-time kinematic (RTK). Multi-constellation use can increase availability in areas with limited sky view such as urban canyons. Multi-frequency can aid in the reduction of multipath and improve accuracy. If the application needs accuracy, these features are readily available.
However, integrity and resiliency are growing needs in commercial applications, especially ones that are in critical operations. Much more can be done to detect jamming and spoofing than what is in standards GNSS receivers today. In our systems, we include an additional software layer called BroadShield, which monitors internal state variables of the receiver, and will alarm on detection. Additional sensors combined with the GNSS receiver such as an inertial measurement unit (IMU), magnetometer, odometer, or even the much stronger Satellite Time and Location (STL) signal offer augmentation during periods of GNSS denial, or in the case of spoofing, authentication of the navigation solution.
While both jamming and spoofing are intentional attacks, they are highly different in their set-up and serve very different purposes. Due to their simplicity, most jamming attacks can be mitigated thanks to adaptive filtering or pulse blanking. On the other hand, spoofing is a malicious attack, highly complicated, and requires knowledge of the GNSS signal structure as well as precise timing and positioning.
The question is thus whether one should emphasize navigation accuracy over the ability to output a position (jamming case) or the possibility to output a completely erroneous position (spoofing case). The answer lies, obviously, in the end application and the coupling of GNSS receivers with other systems. High-precision non-life-critical applications should emphasize navigation accuracy while implementing simple jammer filtering strategies. Life-critical applications, being often coupled with other systems, should ensure the reliability of the solution even if that means being unable to compute a position due potential threats.
Q: Do you have GPS/inertial navigation system (INS) test capabilities?
The CAST-3000 EGI integration system produces GPS RF signals commensurate with simulated IMU sensor data to provide repeatable testing in the integration laboratory for a wide range of military and government applications.
CAST GNSS/INS simulators generate high-fidelity signals required for emulating the legacy GPS signals as well as those used by next-generation navigation technologies. This is because our sole business focus is supplying GNSS simulators, GNSS/INS test equipment, and GNSS/INS support services to government and military avionics laboratories, prime contractors, and GNSS receiver manufacturers. For 35 years we have provided off-the-shelf products to both the government and U.S. major defense contractors.
CAST EGI integration tools are used by Northrop Grumman and Honeywell and are now also being used in integration laboratories worldwide. Our equipment supports system integration in major weapons platform labs and development at major military contractor labs. CAST simulators produce high-quality, accurate signals that are used in government, military and commercial labs around the globe.
Our NCS TITAN GNSS simulator is able to emulate the presence of IMUs and micro electro-mechanical systems (MEMS) sensors with the optional available real-time IMU/Sensor Emulation Package (SEP). The SEP upgrades the TITAN to support the simulation of inertial sensors, which nowadays are implemented as MEMS, among others, and of other common aiding sensors. To obtain more accurate positioning for location-based services and navigation, GNSS chipset and receiver manufacturers as well as system integrators combine more and more GNSS navigation with such sensor fusion or signals of opportunity.
The optional SEP enables controlled and progressive testing of sensor-fusion algorithms when used with NCS Control Center operating software. This software supplies the SEP with an internally- or externally-generated center-of-gravity (CoG) trajectory for the device under test.
The various sensor models to be emulated by the SEP run within the Control Center software. The device under test (vehicle) input trajectory at the CoG passes through the sensor model, which in turn generates the appropriate sensor output, by taking into account the corresponding error model for each sensor defined.
We have added the capability to emulate INS/IMU data in addition to GNSS signals to our Constellator simulator, to offer to the customers a complete testing platform. Constellator can simulate up to six gyrometers and six accelerometers. The attitude of each sensor is defined with respect to the vehicle axes. Deterministic errors can be configured to simulate the axis misalignment and scale factors, and biases can be defined in order to simulate realistic sensors. Stochastic error models are also available such as random walk or Gauss-Markov models for each sensor (gyrometer or accelerometer) to improve the sensor emulation fidelity.
Q: Do you have detailed scenarios for jamming and spoofing in timing use of GNSS receivers, that is, involving time synchronization for telecommunications companies?
The simulated jammer’s signal specification must be very flexible in order to faithfully simulate real-world jamming events. For example, the jammer’s spectral shape should be flexible enough to simulate a Blue Force electronic attack (BFEA) on a GNSS receiver.
Also, the simulator should be able to simulate dynamic scenarios by varying the power of the jammers as a function of their trajectories and as a function of different antenna patterns.
Sometimes when testing receivers, the simulated jammers should replicate pre-recorded waveforms from real world. The ability to play back the pre-recorded IQ-baseband signal in conjunction with GNSS signals is another powerful feature of a simulator. Simulation of spoofing attacks on a GNSS timing receiver is only possible when the GNSS simulator provides fine-grained control of transmitted signal. This includes controlling the offsets on the pseudoranges with additive ramps, as well as individual signal power levels at very precise points in time.
Also, the GNSS simulator must be able to synchronize itself with the live sky’s GNSS signal. Another way to achieve realistic spoofing is to use two simulators controlled independently (that is, full control on constellation, navigation message, propagation time offset, power and so on).
FIGURE 1. Real-world jamming simulation must take into account key factors such as varying jammer power, as a function of their trajectories and antenna patterns. (Image: Skydel)
Q: Please discuss how to simulate a smart spoofer that would generate a replica of a constellation (or all constellations) and then produces two full RF transissions: one that is the true signal, and a strong spoofed signal that pulls the receiver to a false location. Can you simulate the two full multi-band RF ensemble?
Two artificial synchronized scenarios could be created using SatGen signal generator software that can reproduce the GNSS signals from a number of constellations. The user could create two separate signal streams, both starting at exactly the same position and time and using the same constellations, chosen by the user.
The second scenario could then be set to diverge away in position from the first scenario, while staying perfectly synchronized in time. The signal-to-noise ratio of each scenario could be adjusted independently of each other to simulate a spoofing situation where the spoofing signal is much stronger than the real signal. A file containing this twin scenario can be replayed using a LabSat Wideband with two separate RF outputs, each synchronously replaying the two different scenarios. This would closely simulate the actions of a smart spoofer, but in a completely repeatable, and controllable manner.
This could be accomplished by either combining the output of two of our CLAW GPS simulators, or by combining the output of a single CLAW simulator with live-sky signals using passive industry-standard splitters/combiners. The CLAW is able to receive a custom ephemeris download in RINEX format to match either the spoofed live-sky constellation, or to generate a synthesized constellation in the case where two CLAW simulators are being used.
The simulator has a wide RF power adjustment range of over 45-dB, allowing the spoofing signal to be gradually introduced to the primary GPS constellation RF signal. This spoofing simulation could be accomplished with better than 0.5 meter peak-to-peak positioning accuracy and better than 5-ns real-mean-squared (rms) typical UTC (GPS) offset unit-to-unit, allowing the victim receiver to be pulled off of its true (live-sky) position with very high accuracy. Typically, GPS receivers are spoofed easily as long as the UTC timing synchronization is 500-ns or better between the live-sky and spoofed signals.
Timing synchronization to the spoofed victim GPS signal to within nanoseconds is achievable through the external 1PPS reference input, the simulator accepting a position, navigation and timing (PNT) fix in real time via its NMEA serial and 1PPS inputs. This allows capturing a moving victim receiver by estimating its momentary position, then ramping up the spoofer power, and then presenting the victim receiver with alternate position information as required (see Figures 2 and 3).
High position and timing accuracy between the spoofed and live-sky signal is important to prevent and mitigate spoofing detection via UTC phase or position jumps that could happen when the receiver gradually or quickly switches over to the spoofed satellite signals.
FIGURE 2. Spoofing attack on a GPS receiver using a CLAW simulator to spoof a live-sky antenna signal. Initially the spoofer was phase- and frequency-synchronized to UTC(GPS), then spoofer RF power is ramped up, and once the victim GPS receiver is captured, a frequency offset is added to UTC(Spoofer), which pulls the system off-phase. (Figure: Jackson Labs)FIGURE 3. Simulating a spoofing attack on a timing application where the spoofer does not know the exact victim antenna location with certainty. The resulting antenna position offset error (50 meters in this simulation) still allows the victim receiver to be captured, and then causes a time error as satellites move in and out of view even with the spoofer being synchronized to UTC(GPS) at all times. This error is clearly visible in the resulting UTC(Spoofer) output from the victim receiver equipment. (Figure: Jackson Labs)
Q: We want to correctly model and simulate effectiveness of various anti-jamming (AJ) and anti-spoofing (AS) solutions to make informed decisions about which AJ/AS solution is most effective for a specific mission and interference scenario. How can you help?
Live-sky testing on a jamming/spoofing range provides a wealth of data, and reassurance that the system under test does work as intended. Record and playback systems (RPS) under live-sky conditions can allow further evaluation back in the lab, after the live-sky tests are complete. Performance parameters of the RPS may degrade the validity of the signal when played back; signal bandwidth and bit-depth are absolutely key, for example. Recordings that use too few bits will degrade the dynamic range of the recorded signals, so significant care should be taken when selecting an RPS.
Either way, under live-sky or with recorded live-sky, you get what you get. It is extremely difficult to predict what the test parameters actually are. It is perilous to attempt to alter the test parameters after the event. Lab-based or anechoic chamber-based systems have their limitations, but they are repeatable, predictable and tweakable. Again, performance parameters of the simulation system play a key role in the validity of the testing. The ability to calibrate the simulation system to give a repeatable, predictable performance is as important as the realism of the simulation. Carrier-phase accuracy/repeatability among antenna elements and signal timing accuracy are important parameters when evaluating AJ and AS systems.
Q: We had a receiver where the time stamp for any location report would drift off progressively, up to an hour off of the known true location. What might contribute to this? We do not believe this was an intentional threat, but an artifact of nearby electronics or other system conditions. It actually occurred on a pivot irrigation arm in motion, with substantial vibration. The receiver was electrically isolated. The results were repeatable on the pivot arm, but not on our vibration table.
Interesting problem with no obvious answer. Even the worst oscillator will take many months to drift off by up to an hour with no GNSS, even under horrible vibration conditions, so this is an unlikely cause. Is it drift or a jump in error? Nearby electrical noise could cause GNSS denial (jamming), but not erroneous data. That requires spoofing. If you have no reason to believe that it is intentional, that makes spoofing unlikely, but still possible. Is a GNSS repeater or a record/playback GNSS tester operating in the area? These are spoofers, even if they are unintentional.
If this is a precision agriculture application, then an RTK reference station transmitting erroneous data could be the cause. What time-stamping format is used: local time or UTC? An unlikely but possible scenario is the unit is changing time zones so local time jumps an hour. Is there a processor/software app between your output and the actual GNSS receiver? This could introduce errors. What is the position output indicated when the time drift occurs? The best way to diagnose this is to record the time and position output as log files using a laptop PC connected to the serial data.
Q: Do your simulators work as well for testing handheld, consumer-grade GPS? Please discuss the differences in testing techniques or approaches for high-precision vs. mass-market receivers?
We have a range of simulators suitable for all levels of GNSS testing. If you don’t need the high fidelity and wide bandwidth of the LabSat Wideband, then the entry level LabSat 3 will also work with any GNSS device including handheld consumer-grade products.
To fully explore the performance of high-precision receivers, including multipath effects and P-code reception, a wider bandwidth and a greater number of bits would be required to capture and replay all of the available signals. For these applications, we recommend a bandwidth of 56 MHz and at least 4 bits of resolution.
For testing of consumer-grade, handheld devices with simpler RF front ends, we recommend a much reduced bandwidth of around 9 MHz and only 2 bits of resolution. This smaller bandwidth and fidelity will easily reproduce the majority of real-world conditions, and the resulting data files will be much easier to handle.
FIGURE 4. Simulator graphical user interface. (Image: Racelogic)
Q: How many GNSS signals can a software-defined radio produce?
The theoretical limits of a software-defined radio (SDR) are based on four distinct characteristics of the SDR: the digital-to-analog converter’s (DAC’s) bit resolution, the maximum sampling rate, the bandwidth and the number of RF outputs. With most SDRs, available bandwidth is defined by the sampling rate.
With a 16-bit DAC, there is enough dynamic range to generate up to 50 GNSS signals and hundreds of multipath echos (with more than 60 dB of range to accommodate different signal power levels) per RF output.
For example, with a sampling rate of 50 MSps, a 40-MHz wide signal — combining GNSS constellation signals such as GPS L1 C/A, Galileo E1, GLONASS G1 — can be generated. Nowadays, SDRs can have two or more RF outputs and are able to operate with sample rates of 100 MSps or higher. By distributing the GNSS signals across different RF outputs, the entire GNSS spectrum can be covered at a relatively low cost in terms of hardware.
A handful of SDRs can easily be synchronized to form multiple RF output systems. In such cases, the complete range of GNSS signals for all visible satellites can be generated at the same time.
Q: In a dual-frequency receiver would it be possible to still use L1 spoofed/jammed with L2 clean to get an accurate position? Is it possible to do a combination between the two signals in order to save the spoofed/jammed L1?
In principal, it is still possible to use L1 spoofed/jammed with L2 clean in a dual-frequency receiver to get an accurate position. Such receivers are available as off-the-shelf products. These receivers use a special algorithm to detect if a GNSS frequency band is spoofed/jammed and automatically switch over to the clean frequency band. However, this principle can only be applied if the entire GNSS spectrum is not completely jammed. Whether a dual-frequency receiver can still use L1 spoofed/jammed with L2 clean to get an accurate position is therefore finally basically dependent on the overall bandwidth of the interferer/jammer.
With IFEN’s TITAN simulator, it is possible to easily create the corresponding simulation scenarios for the real-time simulation of realistic test scenarios to test the robustness of GNSS receivers against interference/jamming and also spoofing. In doing so, various static and dynamic interference/jamming sources are supported by the simulator’s software.
It is possible to achieve a PNT solution using L2 signals only. This requires reception and decoding of either the military L2 P(Y) signal, or reception of the new but still pre-operational L2C commercial signal. Codeless or semi-codeless commercial L1/L2 receivers rely on tracking the carrier phase on L2 to be able to mitigate effects such as solar flares and ionospheric errors; however, they are not capable of generating a PNT solution with L2-only reception as would be the case under this spoofing/jamming scenario.
P(Y) signal reception on L2 typically requires reception of the coarse acquisition (C/A) signal on L1 prior to tracking P(Y) unless the receiver has its own internal (atomic) time-base synchronized to UTC to the sub-microsecond level.
On-Demand Webinars
Simulation against Jamming and Spoofing: With cyber attacks on the rise, it is more critical now than ever to thoroughly test GPS and GNSS systems against jamming and spoofing.
The SMW200A GNSS simulator adds a high-end solution to the Rohde & Schwarz portfolio of satellite navigation system simulators. It can be extended to up to four RF outputs and allows GNSS signals to be simulated simultaneously in multiple frequency bands for multiple antennas.
The SMW200A can internally simulate a complex interference environment in parallel with GNSS signals.
The instrument was unveiled at ION GNSS+ 2017, which took place Sept. 25-29 in Portland, Oregon:
An increasing number of GNSS receivers are able to process signals from diverse navigation systems such as GPS, GLONASS, Galileo or BeiDou in several frequency bands — and in some cases, with several antennas in parallel — to improve positioning accuracy.
Accuracy can be further improved with differential GNSS (DGNSS) techniques. These techniques are used in applications such as autonomous driving, and they are indispensable for precise and reliable positioning of aircraft during landing approaches. The GNSS receivers used in these applications must undergo extensive tests before deployment in vehicles or aircraft.
The new R&S SMW200A GNSS simulator now offers an innovative test solution for easy generation of complex and highly realistic test scenarios for a wide variety of GNSS applications. To test multi-frequency and multi-antenna systems, users now have access to 72 GNSS channels that can be assigned to up to four RF outputs.
The R&S SMW200A can generate QZSS and SBAS signals as well as GPS, GLONASS, Galileo and BeiDou signals. This solution enables users to quickly and easily verify the position accuracy of their receivers under realistic conditions.
The R&S SMW200A also has an internal noise generator and can generate complex interference scenarios with multiple interferers. All signals (GNSS, noise and interference) are generated directly in the instrument. Additional signal sources for external generation of interference signals are not necessary, considerably simplifying test setups.
No external computer is needed to configure and operate the R&S SMW200A. The integrated, intuitive graphical user interface (GUI) allows users to generate GNSS scenarios quickly and easily. Thanks to the multitude of instrument options, the solution can be optimally adapted to individual user requirements.
The R&S SMW200A is an extensible, future-proof platform ready to implement future test requirements such as testing new GNSS signals.
The R&S SMW200A with the new GNSS options is now available from Rohde & Schwarz.
VersaSync is a high-performance GPS master clock and network time server that delivers accurate, software configurable time and frequency signals under all circumstances, including GNSS-denied environments. Its compact size and high level of ruggedization make VersaSync suitable for mobile applications in harsh environments. Its small footprint allows for easy integration of the time and frequency functionality into systems architecture.
VersaSync accommodates an OCXO, a high-performance OCXO or a CSAC oscillator, allowing it to maintain frequency and time accuracy for long periods of GPS/GNSS outage. It can be re-synchronized by an external reference. VersaSync is available with a C/A L1 GPS receiver or with an L1/L2 SAASM receiver. An extension slot accommodates additional timing interfaces.
VersaSync physical inputs and outputs are software configurable and can adapt to various application requirements. I/O pins can be configured as TTL, 10 V pulse, RS232, RS485. This allows VersaSync to provide a high number of outputs of the same type, while still fitting into a small form factor. If the combination of software configurable outputs is not enough, VersaSync can accommodate an option board (within the same form factor), designed to customer requirements.
Because of its high level of ruggedization, VersaSync provides exceptional intrinsic reliability. Strong status monitoring capability, either locally or remotely, allows quick fault diagnoses. An internal, exportable log can be accessed.
Verasync Attributes
Low size, weight and power
Ruggedized (MIL-STD-810G)
High versatility with software configurable inputs/outputs
Design can be efficiently customized to match specific customer requirements
Easy integration due to small footprint and low power consumption
NTP/PTP precise time transfer over Ethernet, including security protocols that prevent network vulnerabilities
Low phase noise 10-MHz frequency distribution
Configurable pulse signals, including IRIG or HaveQuick timecodes
The Simceiver by IP Solutions now features Beidou as a simulated signal with access to full parameters rather than the record and playback function used previously.
The Simceiver is part of the Replicator system, a multi-frequency, multi-system GNSS simulator for advanced research and development, equipment testing and education. It can also function as a recording, playback and signal analysis instrument.
The Replicator is the result of a collaboration with the Japan Aerospace Exploration Agency (JAXA).
Besides the Simceiver hardware unit, components include the ReGen control software for real-time simulation, Streamer control software for recording and playback and ARAMIS software receiver for signal analysis.
The 24-channel Replicator provides real-time generation of GNSS signals, recording and playback of dual-frequency GNSS RF signals, and GNSS RF signal analysis with JAXA COSMODE ionospheric scintillation monitor.
The Replicator offers real-time simulation of dual-frequency GPS, GLONASS, BeiDou or GPS+GLONASS, GPS+BeiDou, GPS+Galileo signals. Comprehensive simulation models include atmosphere, multipath, and more. Also available is signal analysis based on JAXA COSMODE ionospheric scintillation monitor.
Two or more units can be used to simulate, record and playback more signals at the same time. Simulated and recorded signals can be stored in digitized format, analyzed by a MATLAB software receiver and played back as RF at any time.
ReplicatorAdvantages
User defined models with ANSI C API
Real-time simulation
Record and playback
GNSS signal analysis
Upgradable to more features , signals and frequencies for the difference in price.
4- and 7-channel boards for software GNSS receivers
The NT1065_USB3 and NT1065/66_USB3 multi-channel GNSS RF front-end boards are based on NTLab’s RF ICs: NT1065 (4 channels for GPS/GLONASS/Galileo/Beidou/IRNSS/QZSS, L1/L2/L3/L5 bands) and new NT1066 (2 channels for GPS/GLONASS/Galileo/Beidou/IRNSS/QZSS, L1/L2/L3/L5 bands and 1 channel for IRNSS S-band). Both boards support USB3 connection, thus allowing users to process captured satellite signals on a PC or DSP platform.
NT1065_USB3 BOARD
Multi-system multi-band 4-channel GNSS RF front end based on NT1065.
Features
IF bandwidth up to 32MHz for each channel
Acquisition of wideband signals up to 64-MHz (such as Galileo E5) with 2 coherent channels
Built-in 2-bit ADC
USB3 interface (up to 800-Mbit/s)
Ability to connect 4x CRPA
NT1065/66_USB3 BOARD
Multi-system multi-band 7-channel GNSS RF front end based on NT1065 plus new NT1066.
Features
All NT1065_USB3 features, plus:
2 additional L1/L2 GNSS channels
IRNSS S-band channel
Product Support
Both boards are accompanied by comprehensive software and manuals:
GUI for NT1065/66 registers access and USB3 data capture (Windows 7/8/8.1/10 and Linux Ubuntu 16.04 compatible)
Designed to test receivers against current and future signals
Constellator features top-end processing performance and RF quality and offers flexibility in simulation control. It performs fair-weather tests, but also is designed to subject receivers to suboptimal conditions, extreme situations and combinations of errors difficult to access in real-world tests — all of it finely controlled and indefinitely repeatable.
At constellator’s core is software, ensuring that all future constellations, satellites and codes can be handled. Most functional upgrades will then be software-only.
Constellator is used in aerospace and defense (among others) for multi-antenna receiver testing for spacecraft launchers, satellite onboard receiver testing (telecom and observation) and defense UAV receiver testing.
Constellator includes four spatial reference frames and trajectory editors for ground, marine, aerial and spatial motion and import facility. With hardware-in-the-loop, it receives position updates from test rigs in real time and generates corresponding GNSS signals and messages.
Propagation issues can be simulated at individual signal level with different models provided for ionosphere and troposphere.
Satellite error modeling options include orbital errors, onboard clock errors, satellite electronics (front-end) defects, satellite dysfunctions and signal fade, disappearance and “evil waveform” incidents.
Constellator Features
128 channels (extensible) delivering high-quality satellite signals on six distinct frequencies (L and S band)
Hardware-in-the-loop testing at 10- to 100-Hz refresh rates
Extensive simulation options:
Full-time and location control
Receiver trajectories with extreme dynamics
Background noise, interference and jamming/spoofing (two units)
The PwrPak7-E1 contains an Epson G320N micro-electro-mechanical system (MEMS) inertial measurement unit (IMU) to deliver NovAtel SPAN technology in an integrated, single-box solution. It has a powerful OEM7 GNSS engine, integrated MEMS IMU, built in Wi-Fi, onboard NTRIP client and server support and onboard internal storage. The PwrPak7-E1 also has enhanced connection options including serial, USB, CAN and Ethernet.
SPAN Technology
Synchronous Position, Attitude and Navigation (SPAN) technology brings together two different but complementary technologies: GNSS positioning and inertial navigation. The absolute accuracy of GNSS positioning and the stability of IMU gyro and accelerometer measurements are tightly coupled to provide an exceptional 3D navigation solution that is stable and continuously available, even through periods when satellite signals are blocked.
The CAST-5000 produces a single coherent wavefront of GPS RF signals to provide repeatable testing in the laboratory environment or anechoic chamber. The system generates up to seven independent, coherent simulations that reference a single point.With an intercard carrier-phase error of less than one centimeter, the CAST-5000 is extremely accurate.
The system generates a wavefront of GPS when its GPS RF generator cards are operated in a ganged configuration. Each generator card provides a set of GPS satellites coherent with the overall configuration. Several RF generator cards may be utilized together, ensuring phase coherence among the bank of signal generator cards.
The CAST-5000 is the only Controlled Reception Pattern Antenna (CRPA) tester that allows a full end-to-end test of the antenna system. The CRPA antenna, antenna electronics and the GPS receiver can be tested as a unit with or without radiating signals.
CAST-5000 Features
Generates single coherent wavefront of GPS
6 degrees of freedom (DOF) motion generation capability
A next-generation high-precision module for robots, drones
The UM482 is an all-system multi- frequency high-precision heading module with a small footprint. It supports the satellite signals GPS L1/L2, BDS B1/ B2, GLONASS L1/L2, GALI LEO E1/ E5b and SBAS. It is designed for applications such as robot, drone, intelligent drive and mechanical control.
The UM482 GNSS RTK module adopts Unicore’s new-generation Nebulas II chip and UGypsophila real-time kinematic (RTK) algorithm. Based on high-performance data-sharing technology and super-simplified operation system of the Nebulas II chip, the UGypsophila RTK algorithm dramatically optimizes matrix processing. It can involve all satellites from GPS, BDS, GLONASS and Galileo in RTK and heading processing, shorten RTK and heading initialization time to 5 seconds and significantly improve the reliability and accuracy of RTK and heading.
Furthermore, the UM482 integrates the onboard micro-electro-mechanical (MEMS) chip and U-Fusion integrated navigation algorithm, resulting in optimized continuity and reliability of accurate heading and positioning output in tough environments such as city canyons, tunnels and overpasses. Inputs of odometer and external higher performance inertial components are supported.
The HG4930 is a very high-performance micro-electro-mechanical system (MEMS) based inertial measurement unit (IMU) designed to meet the needs of applications across various markets including agriculture, industrial equipment, robotics, survey/mapping, stabilized platforms, transportation, UAVs and UGVs.
With industry-standard communication interfaces, the HG4930 is easily integrated into a variety of architectures. The extremely small size, light weight and low power make the HG4930 ideal for most applications.
The HG4930 includes MEMS gyroscopes and accelerometers. It employs an internal environmental isolation system to attenuate unwanted inputs commonly encountered in real-world applications.
The internal isolation and other proprietary design features ensure the HG4930 is rugged enough to meet the needs of demanding users.
The HG4930 is not ITAR controlled. Its Export Control Classification Number (ECCN) is 7A994.
Example Applications
Aiding a camera pod to track a desired object: For example, a television viewing enhancement systems used in sports broadcasting.
Integration with GPS/GNSS to navigate an object from point A to point B: IMU performance is key; errors grow quickly without GPS/GNSS (such as in forested areas, underwater, dense urban).
Dynamic antenna platform stabilization: IMU measures small perturbations of a platform under motion (including vibration and shock) and feeds those measurements into a control system that then corrects and stabilizes the platform; without an IMU, communication can be degraded or lost.
Robots: Enables robots to navigate indoors with other aiding sources (such as radar or lidar); similar concept to GPS/GNSS aiding.
Supports restricted and classified signals from GPS, Galileo
The Spirent GSS9000 multi-frequency, multi-GNSS RF constellation simulator can simulate signals from all GNSS and regional navigation. The GSS9000 offers a four-fold increase in RF signal iteration rate (SIR) over Spirent’s GSS8000 simulator. The GSS9000 SIR is 1000 Hz (1ms), enabling higher dynamic simulations with more accuracy and fidelity. It includes support for restricted and classified signals from the GPS and Galileo systems as well as advanced capabilities for ultra-high dynamics. It can evaluate resilience of navigation systems to interference and spoofing attacks, and has the flexibility to reconfigure constellations, channels and frequencies between test runs or test cases.
Captures and replays GNSS signals at high resolution
The LabSat 3 Wideband record-and replay-device is small and battery-powered with a removable solid-state disk. It allows users to gather detailed, real-world satellite data and replay the signals on the bench.
Its recording bandwidth of 56 MHz allows for the capture of a wide range of live-sky satellite signals. Depending on the desired bandwidth, recording resolution can be set to 2, 4 or 6 bit. The GNSS frequency guide on the LabSat website shows exactly which signals can be recorded and at which resolution. It also has spare capacity for future planned signals.
Even with this increased capacity over the original LabSat 3, the new simulator remains easy to use: one-touch recording, no connection to PC required, battery powered for up to two hours, and with a removable 1-TB solid-state hard drive that can be replaced in no time, the LabSat 3 Wideband is convenient to use. It measures a compact 167 x 128 x 46 millimeters and weighs 1.2 kilograms.
Live-sky Signals Captured
LabSat 3 Wideband can record and replay the following signals:
Stanford Research Systems (SRS) rubidium frequency standards have excellent aging characteristics, extremely low phase noise and outstanding reliability.
The FS725 benchtop instrument is designed for calibration and research and development (R&D) laboratories, or any application requiring a precision frequency standard, such as metrology laboratories.
The FS725 unit integrates a rubidium oscillator (SRS model PRS10), a low-noise universal AC power supply, and distribution amplifiers in a compact half-width 2U chassis. It provides stable and reliable performance, with an estimated 20-year aging of less than 5 x 10-9 and a demonstrated rubidium oscillator MTBF (mean time between failures) of more than 200,000 hours.
It has two 10-MHz outputs and one 5-MHz output with exceptionally low phase noise (–130 dBc/Hz at 10-Hz offset) and 1 second Allan Variance (<2 x 10-11). The FS725 can be phase-locked to an external 1-pps reference (like GPS) providing Stratum 1 performance. A 1-pps output is also provided that has less than 1 nanosecond of jitter, and can be set with 1-nanosecond resolution.
