Spirent’s simulation systems have changed significantly from their technology beginnings, which can be traced back to World War II radars. The company and its technology have evolved to keep pace with today’s growing population of GNSS constellations and to meet the challenges that receiver manufacturers and users encounter in an ever-complex integrated GNSS environment.
In the early days of GPS when there were only enough satellites for a fix at odd times of the day or night, these nighttime expeditions were the only form of testing that we could get our hands on. Then as the constellation grew, we were delighted when eventually you could do open sky testing whenever you needed. It never even occurred to us that more exhaustive, more complex testing would become essential as time progressed.
If you walked into any GNSS manufacturer’s testing facility nowadays, the ubiquitous test rack at the heart of most test validation systems might well include a Spirent simulator of some vintage. I recall when we were bringing up receivers in engineering, one of our concerns was how the heck could we afford another one of these beasts for the guys down in production? After we already broke the bank when we managed to convince management that we couldn’t live without a Spirent, we were wondering who we’d push to the front of the line to tell the boss that we had to buy yet another one for the guys on the production line. At one time before a cut-down single channel box became available, we shared our simulator with production who operated the system remotely and a coax run provided RF onto the production floor. We still did open sky testing in R&D, but the complex validation scenarios would have been impossible for the team without our Spirent simulation system.
Recently I got to wondering where Spirent had come from and how come they had become one of the leading players in GNSS simulation. I did recall that they were UK based, that there were a number of name changes and that at one stage they also had receiver capability. So I got talking with John Pottle who’s always been my marketing window into Spirent, and Peter Boulton who’s been my principle technical contact. I was interested in Spirent’s background, their engineering capability, how they got where they are now and where they plan to go in the future.
Its not surprising that Spirent’s roots go way back in England to the period of the second world war. England developed radar as an early warning system that helped win the air combat Battle of Britain. Following the extensive blitz bombing of London, the UK government subsequently re-located the radar technology team well out of harm’s way to the distant and more secure southern tip of England, and that technology team formed the core of a high-tech group based in Paignton, Devon which eventually evolved to focus on GNSS simulation.
Southern England – Paignton base for Spirent.
It’s a nice area to live in, with fewer people, smaller towns and a very pleasant climate. So the technology guys and their families hung around and the government facility became Standard Telephones (STC) and Cables Defence Systems. Focusing in those days on travelling wave guides, cathode ray tubes, and radar amplifiers and the like, this business grew to include solid-state amplifiers, satellite communications and repeaters for fiber-optic networks. This all needed test equipment and a test division grew up to service STC’s technology groups.
As GPS came on line, the UK Government Royal Aircraft Establishment (RAE) needed GPS simulation capability to verify GPS system performance, and STC came up with a test system equipped with 6 dual-frequency satellite signal sources with additional jamming sources and a range of military data interfaces. The computer operating system was VMS running on a Digital Microvax2 platform, the software was written in DEC Fortran and the DOS-like user interface had textual menus with a graphics terminal for X-Y plots. Just like we had racks of equipment for the original single channel GPS receivers, GPS simulation systems started in the same way.
RAE GPS Simulation System 1987.
In parallel STC was also working on a contract to develop a military GPS receiver, and several of the GPS ASICS used in that receiver found their way into the simulator. Simultaneously, the RAE contract was extended to include provision of full SA-A/S capability, which was delivered in 1988. This classified system was used to formally evaluate the Rockwell-Collins 3A receiver SA-A/S implementation – at the time this test system was the only one available capable of emulating all the features of SA-A/S.
As it became clear in1988 that GPS would have a wider commercial market, STC began to invest in simulation systems for commercial receiver manufacturers.
STR2740 Simulator 1989.
STR2760 Simulator 1991.
With dual frequency and up to 10 satellite channels, the STR2740 was still quite large as it was based on the floor standing Microvax2. Porting the software to a desktop VMS workstation gave us the more familiar STR2760 that was first displayed at the ION-GPS-1991 convention in Albuquerque. This initial unit was actually purchased from the ION display show floor and STC had to hustle to quickly make more!
Then ownership passed to Northern Telecom in Canada, who was initially interested in STC’s fibre-optic communications technology and products. After a few years, Northern Telecom changed its name to Nortel – so then we all started talking about ‘Nortel simulators’. The next phase of internal development re-tuned the technology and the resulting 1997 STR4760 simulator boasted double the channel capacity and enabled the inclusion of GLONASS and SBAS capability.
STR4760 Simulator 1997.
In the same timeframe, development of a Controlled Radiation Pattern Antenna (CRPA) was underway in Paignton, but this didn’t quite fit with a business focus on testing, so the CRPA line was sold to Cossor, which was subsequently merged with Raytheon — and the well-known GAS-1 mil-spec CRPA was the outcome. The GPS receiver technology went along with the CRPA to Cossor and ultimately on to Raytheon.
In 1997 the Nortel name also disappeared as Bowthorpe in UK became the new owners and the group became known as ‘Global Simulation Systems’ and we then had “GSS” simulators for a period, but by 2000 the parent company changed its name to Spirent, and that name seems to have stuck.
When SA was switched off in 2000, the potential for commercial GPS became apparent to the Spirent team and this fired up investment in a brand new range of products for the commercial GPS L1 C/A code marketplace – units can often be found in use for single channel production testing, whilst other multi-channel simulators are in use for commercial, pre-production, R&D and verification.
Full L2C, L5 and M-code GPS modernisation was introduced in 2004 while retaining essential systems and scenarios backward compatibility. Spirent’s approach has been to endeavour to get to market early with new signal capability for early adopters.
Support for all Galileo signals and services arrived in 2006 and the GSS8000 series in 2008 added a wide range of additional signal generation capabilities as well as GLONASS L1/L2 and QZSS.
GSS8000 Series Simulator 2008.
SimGEN has been the Microsoft Windows user interface provided by Spirent since around 2002.
SimGEN interfaces to external receivers, and enables external vehicle trajectory input via various interfaces. High speed remote control is also possible and logging/displaying/plotting is also available for report generation and results analysis.
So today, Spirent has accumulated a significant range of simulation capabilities:
Galileo RF constellation simulators for all frequencies & services
GPS L1 C/A and P/Y, L2C, L5, M-Code, M-Noise, L1C
GPS SBAS (MSAS, WAAS, EGNOS, Gagan)
GLONASS L1/L2
QZSS L1 C/A, SAIF, L1c, L2c and L5 signals
R&D systems for the IRNSS regional system program
Automotive sensor simulation
SimGEN emulation of Aircraft Landing Augmentation System (GBAS)
SimINERTIAL adds stimulation of test Inputs for several types of inertial sensors.
Equipment for both GNSS manufacturing and field testing
With around 25 in-house engineers and a number of outside consultants, the technical team is not huge. But with 27 years of accumulated experience in GNSS simulation, and a large ‘vault’ of key technologies, Spirent is well positioned for the challenges that the world’s multiple, evolving GNSS constellations are presenting to manufacturers.
So what’s next for the Spirent simulator business? Well the Chinese COMPASS constellation is coming on fast, so even though there is still no complete, usable public ICD available, Spirent has adopted the same approach used when release of the Galileo ICD was restricted by ESA – Spirent supplies a COMPASS simulator which has the ‘real’ modulation and frequencies, but the customer inputs the navigation messages.
Spirent is also getting some traction from users who want simulation systems to model specific applications – like car motion sensors to simulate the inputs of in-vehicle navigation system, or full ground segment monitoring and fully integrated message generation for GBAS aircraft landing systems or simulation designed for testing of integrated GPS/Inertial systems.
The days of relying on GNSS alone for navigation and positioning may be fast disappearing, so its likely that things will get even more complex. While there may be some significant questions, such as which combination of GNSS frequencies/signals/constellations to choose from to optimise performance for a particular application, the focus for developers is getting much broader than GNSS or even multi-GNSS alone. Or you could say that the problem has shifted from proving GPS receiver performance alone, to proving, and improving systems and applications performance to meet increasingly demanding end-user needs.
For example, in defence applications where integrity and resilience are key focus areas, inertial navigation is used to complement GNSS, and adaptive antenna technology helps to overcome intentional interference threats. In commercial markets, getting good accuracy everywhere has led to hybrid approaches that include cellular and Wi-Fi positioning and augmentation from MEMS inertial sensors.
Spirent’s product road maps appear to reflect this shift in customer needs. This year we should expect to see Spirent GNSS/inertial test capability for commercial inertial sensors, and also manufacturing and functional testing of consumer devices that include not only GNSS but also Wi-Fi, Bluetooth and other emerging technologies such as near-field communications (NFC) contactless technologies.
So a varied range of GNSS simulation capabilities which match up to the challenges which users face in the real world — and with over 800 simulations systems supplied world-wide, Spirent is surely setting the pace for the evolving GNSS & systems simulation marketplace.
By Alison Brown, Jarrett Redd, and Mark-Anthony Hutton
GNSS signal simulators can be expensive and beyond the limited budgets of many researchers. In this month’s column, we look at one company’s approach to providing GNSS signal simulation at a low cost — one that virtually any researcher can afford.
INNOVATION INSIGHTS by Richard Langley
WHY DO WE SIMULATE REALITY in mathematics, science, engineering, and other pursuits — even in our recreational activities? Well, we do it for a variety of reasons. In mathematics and science, we try to comprehend reality, which is complicated and variable and often has some degree of randomness. We build mathematical models of physical, chemical, or biological processes to better understand them or to predict a particular outcome given some initial conditions. The model may contain a stochastic component to reflect a degree of uncertainty associated with the processes. Weather forecasting is a prime example. Typically, the models are run on a computer where the model parameters and initial conditions can be readily adjusted and the varying outcomes analyzed.
Simulations of reality are often used in teaching where students can more easily grasp the behavior of complicated systems whether they be in the natural sciences or in economics or the social sciences. In medical education, simulated human patients are used initially because it is safer than having students operate on real patients. Similarly, flight simulators are used for the training of pilots because it is cheaper and safer than using real aircraft and a wide variety of “what if” scenarios can be experienced.
Simulation is used for a range of engineering activities to see how an existing system behaves under different conditions because it is faster or cheaper than performing tests in the “real world.” It can also be used to estimate how a proposed new system might behave before it becomes a reality — looking at traffic flow in road networks, for example.
We also use simulation for recreation, whether it is playing with the latest computer game or improving our swing with a golf simulator. And simulation is a mainstay of the movie industry.
But getting back to engineering and the main interest of this magazine, simulation is a useful technique in the design and operation of equipment used with global navigation satellite systems. With a radio frequency simulator, we can mimic the radio signals generated by the satellites. These devices allow us to define scenarios, including receiver trajectories, and to replay them while varying the operating parameters of the receiver. Some simulators allow us to record live signals and then to play them back under different assumed conditions.
However, such GNSS signal simulators can be expensive and beyond the limited budgets of many researchers. In this month’s column, we look at one company’s approach to providing GNSS signal simulation at a low cost — one that virtually any researcher can afford.
As the noted French sociologist and philosopher, Jean Baudrillard, pessimistically once said: “We live in a world where there is more and more information, and less and less meaning.” In the field of GNSS engineering, at least, simulation is helping to stem the tide and give us a better understanding of reality.
“Innovation” features discussions about advances in GPS technology, its applications, and the fundamentals of GPS positioning. The column is coordinated by Richard Langley, Department of Geodesy and Geomatics Engineering, University of New Brunswick. To contact him with topic ideas, email him at lang @ unb.ca.
Embedded GPS receivers have become commonplace with the proliferation of GPS navigation systems into all but the least expensive vehicle and cell-phone lines. As more manufacturers embed low-cost GPS receivers into their products, the need for low-cost GPS signal simulators has also grown. Controlled virtual testing is vital in ensuring the expected system performance.
Many GPS signal generators are available that are designed specifically for high-volume production test applications for devices that use commercial GPS/SBAS, GLONASS, and Galileo receivers. Often the cost of these high-end simulators is beyond the reach of small companies or universities. In response to this need, we have developed our low-cost, software-defined radio (SDR)-based GPS Signal Architect Test Set to address a broad range of research, academic, industrial, and defense applications. The system is designed to be flexible, scalable, and most importantly, inexpensive.
Our test set leverages the capabilities of the Universal Software Radio Peripheral (USRP) radio and our GPS Signal Simulation Toolbox to provide users with a GPS signal generation capability at a much lower cost than currently available on the market. The combination of the GPS signal simulation software coupled with the record and playback capability of the USRP makes for an extremely low-cost, yet highly flexible, GPS signal simulation capability.
FIGURE 1 shows the GPS signal simulator hardware. It is designed for use with commercial software-defined radios and is based on our GPS Signal Simulation Toolbox.
FIGURE 1. GPS signal simulator hardware.
Toolbox. The Toolbox is a complete set of GPS signal simulation, test, and analysis tools. This Matlab-based signal simulation toolbox simulates the effect of the signal degradation on a conventional commercial GPS receiver, including the effect of the ionospheric activity on the code and carrier tracking loops such as losing lock or cycle slipping. The Toolbox’s geographic tools facilitate the transformation of data between the various coordinate systems commonly used in GPS research, including latitude-longitude-altitude; WGS 84 Earth-centered, Earth-fixed (ECEF); north-east-down; and body-fixed reference frames. It also provides tools to read GPS almanacs and ephemerides and compute ECEF and line-of-sight vectors to GPS satellites as a function of user position and time. The receiver design and analysis tools model different receiver architectures and simulate different error scenarios by providing tracking and navigation algorithms, including phase lock loops and delay lock loops.
The user-configurable options allow the operator to define virtually all aspects of a GPS signal environment, including the GPS spreading code(s), navigation message, and interference scenarios. Such flexibility is particularly useful in simulating GPS jamming environments, where time, resources, and repeatability are generally scarce.
Because these tools are linked directly to Matlab, it is relatively simple to define and implement new signal components as they become available. Of primary interest are the GPS modernization codes as well as those of other global navigation satellite systems (GNSS). Also of interest are new and exotic categories of jammers, including frequency-modulated, amplitude-modulated, phase-modulated, and frequency-swept jammers.
An early version of the toolbox was reviewed in a previous Innovation column (see Further Reading).
Configuration. In the configuration shown in Figure 1, the signal control unit (SCU) is used to control the radio for record and playback operation. The USRP includes a 10-MHz frequency standard as well as an input for an external reference clock. The GPS Signal Architect software can produce custom GPS scenario data files, which can use the USRP to produce a GPS signal at RF.
This article provides a review of how the signal simulator uses the USRP family of radios as low-cost RF record and playback devices using the Signal Architect files. In addition, the hardware design and supported signals are described and test results are presented showing the USRP providing simulated GPS signals to conventional GPS user equipment.
Radio Hardware
The USRP radio family provides an inexpensive development platform for software-defined radios. The USRP can also be used to record and play back the GPS signal in a static or mobile environment. The system operator can then reproduce the signal on the bench either from a simulated profile or from a previously recorded test environment. An advantage of the USRP is that it supports a wideband transceiver front-end that can accommodate the full 20 MHz of the GPS signal band and can be tuned to operate at any of the GPS signal frequencies (L1 at 1575.42 MHz, L2 at 1227.60 MHz, or L5 at 1176.45 MHz). This allows record and playback of both the civil and military GPS codes.
While the GPS Signal Architect tools can be easily adapted for use with any commercial SDR, the USRP family was chosen because of its reasonable price, quality construction, and extensive support by the GNU Radio project.
USRPs are SDRs, which can, in principle, transmit or receive signals on any frequency under software control. Typically, USRPs connect to a host computer through a high-speed USB or gigabit Ethernet link, which the host-based software uses to control the USRP hardware and to transmit or receive data. Some USRP models also integrate the general functionality of a host computer with an embedded processor that allows the USRP to operate in a standalone fashion. The USRP hardware is controlled through a hardware driver, which supports Linux, MacOS, and Windows platforms. A framework running on the host computer then accesses the USRP through the driver. Several frameworks, including GNU Radio (a free software toolkit for learning about, building, and deploying SDR systems developed under the GNU Project — “GNU” is a recursive acronym that stands for “GNU’s Not Unix”), LabView, Matlab, and Simulink, use the driver. The driver’s functionality can also be accessed directly with an application programming interface (API), which provides native support for C++. Any other language that can import C++ functions can also use the driver. This is accomplished in Python through the Simplified Wrapper and Interface Generator, for example. The API allows users to develop their own custom frameworks, as we did with our SCU.
Of the available USRP radios, the N210 was chosen because it has the highest sample rate, greatest flexibility, and largest capacity for modification (see FIGURE 2).
FIGURE 2. Univeral Software Radio Peripheral.
The USRP provides an interface between high-speed analog to digital converters, high-speed digital to analog converters, and an Ethernet interface, as previously mentioned. Daughterboards available for the USRP provide an interface from the baseband signals present at the data converters to the GPS frequency bands and vice versa.
A daughterboard (or daughtercard or piggyback board) is a circuit board meant to be an extension or “daughter” of a motherboard. The USRP uses interchangeable daughterboards, plugging into the main board, to serve as the RF front end. Several classes of daughterboard modules exist: receivers, transmitters, and transceivers. Transmitter daughterboard modules can modulate an output signal to a higher frequency; receiver daughterboard modules can acquire an RF signal and convert it to baseband; and transceiver daughterboard modules combine the functionality of a both a transmitter and receiver.
For this project, a WBX (wide bandwidth) transceiver daughterboard was installed in the USRP. The tunable range of the WBX (50 MHz to 2.2 GHz) covers all the current GNSS frequencies. An RF pre-filter is used to band-limit the GNSS signals to the sample rate selected for use in the SCU to avoid spectral folding from the N210 40-MHz channel bandwidth. For example, a 2-MHz filter centered at L1 is optimal based on the Nyquist sampling frequency of 2 MHz of both the in-phase and quadrature (I/Q) components of the signal. If sampling at 20 MHz, then a 20-MHz pre-filter should be used.
Signal Control Unit
The SCU includes a Linux single-board computer with software developed to run under the GNU Radio Companion (an open-source graphical tool for creating signal flow graphs and generating flow-graph source code using the GNU Radio libraries) and management of the GNU SDR for RF record and playback under control of the GPS Signal Architect software through an Ethernet connection. This enables the user to tap into the excellent USRP community support for his or her project and benefit from the close relationship between the GNU Radio project and the USRP manufacturer. The Ethernet connection is also used to download and upload recorded or simulated signal files from the Signal Architect signal simulation software.
Signal Simulation Software
The GPS Signal Architect hardware and software provides users with a Matlab-based GPS signal generation capability. If our Matlab GPS Toolbox is provided, the Signal Architect GPS simulation can be run under the Matlab environment. For the non-Matlab user, the Signal Architect software is bundled as a stand-alone executable. The signal simulation flow is depicted in FIGURE 3.
FIGURE 3. Signal Architect simulation flow. (Click to enlarge.)
GUI. Using a simple, intuitive graphical user interface (GUI), the user specifies a trajectory and a complete set of simulation parameters to create an I/Q data file (see FIGURE 4). The user specifies a trajectory either from an NMEA file (most GPS receivers use the National Marine Electronics Association 0183 interface standard for logging positions and other data) or a KML file from Google Earth (Google’s Keyhole Markup Language has become a standard for describing geographically referenced features), and an almanac file used to define GPS satellites to be simulated. The user defines the mask angle for the satellite selection and the noise figure to be simulated. The Signal Architect software then generates a simulated digital storage file, including the selected pseudorandom noise codes (C/A and/or the unencrypted military P or M′ codes).
FIGURE 4. Signal Architect graphical user interface. (Click to enlarge.)TABLE 1. Signal simulator system specifications.
Scenarios. The Signal Architect software also ships with preloaded scenario files that the user can run right out of the box into the SCU using the USRP. The Signal Architect software supports computers with multi-core processors and will automatically configure itself to run on all available processors. The Signal Architect software will generate either static or dynamic simulation profiles. The Signal Architect GUI allows the operator to easily modify a wide range of scenario variables from the pre-set defaults. Complete scenarios are easily shared between signal simulation systems, supporting collaborative testing between similar projects and reducing the amount of time spent developing test tools.
The signal data file can then be used for subsequent analysis within Matlab using the Matlab GPS Toolbox, or can be provided to the SCU and USRP to create a GPS signal suitable for playback into a GPS receiver. If the Matlab GPS Toolbox is available, the user has complete flexibility to manipulate the signal at various stages of generation or post-generation to simulate GPS anomalies. Without the toolbox, the user is restricted to using only the standard error modeling provided by the compiled Signal Architect code.
Simulation Test Results
To demonstrate the high fidelity of our Signal Architect signal record and playback capability, a series of stationary GPS simulations were run. In these tests, the USRP was used to record and play back GPS C/A-code signals at the L1 band (1575.42 MHz). The SCU and USRP were connected to a rooftop-mounted GPS L1 antenna. The GPS signal was split between a commercial GPS receiver and the USRP to allow the operator to monitor the GPS receiver while the USRP was recording the GPS signal.
In record mode, the I/Q data is written from the USRP to a file on the SCU. In playback mode, the data is read from the file by the USRP to generate the RF signal. The RF signals are output to the GPS receiver through an external variable attenuator. The attenuator allows the operator to adjust the signal power into the GPS receiver as different lengths of antenna cable are added or as the signal is split to other GPS receivers.
To demonstrate the GPS Signal Architect Test Set performance, representative data was collected in a series of two laboratory tests. The first test demonstrates the system performance as a record and playback GPS signal simulator. The second test results demonstrate the system performance when using the Signal Architect software to generate custom GPS scenario files for playback into the GPS receiver.
In the first test, the GPS simulator hardware was configured as shown in FIGURE 5. The GPS receiver and USRP were connected to a commercially available antenna. The antenna was positioned at a known location with a clear view of the GPS constellation. The signal from the GPS antenna was split between the GPS receiver and the USRP so that the data could be logged by the receiver software at the same time as it was being recorded by the SCU.
FIGURE 5. GPS Signal Simulator record and playback GPS simulation.
The simulated satellite constellation is shown in FIGURE 6. Seven GPS satellites are in view.
FIGURE 6. Simulated satellite constellation.
The 2-D position error from the simulated signal is shown in FIGURE 7. The errors are representative of the accuracies achievable using GPS C/A-code pseudoranges.
FIGURE 7. North-east (2-D) position error.
We can examine the performance of our test set by looking at plots of the measurements of carrier-to-noise-density ratio (C/N0) from the GPS receiver for both the live sky data and for the recorded signal when played into the GPS receiver by the Signal Simulator for three of the GPS receiver channels (see FIGURE 8). The C/N0 data collected from the GPS antenna is shown in blue, while the C/N0 from the USRP is shown in green.
FIGURE 8. C/N0 record and playback vs. live sky collection.
As we can see, the C/N0 was 1–2 dB lower in playback mode when compared to the data collected from the GPS antenna. The signal loss is due to the 1-bit sampling of the incoming GPS signal by the Signal Architect software. One-bit and 2-bit quantization are used in many commercial GPS receivers. The rule of thumb states that 1-bit quantization degrades the signal-to-noise ratio by 1.96 dB, and 2-bit quantization degrades the signal-to-noise by 0.55 dB. These results show that 1-bit I/Q sampling is sufficient for reproducing GPS L1 C/A-code signals with the USRP.
In the second test, the Signal Architect software was used to generate a 10-minute static GPS C/A-code L1 scenario file. The SCU used the USRP to generate the GPS signal.
Shown in FIGURE 9 are the number of satellites the GPS receiver was able to track. When using the GPS Signal Architect Test Set to play back the scenario file, the GPS receiver was able to track all the simulated satellites in the file. The time necessary for the GPS receiver to acquire and track the satellites is consistent with the performance one would expect from the GPS receiver when connected to an external antenna.
FIGURE 10 shows the C/N0 measurements from the GPS receiver for three of the receiver channels. There were nine satellites in this static scenario file. The C/N0 for all the satellites is stable for the duration of the scenario playback.
FIGURE 9. Number of satellites tracked (digital signal file playback mode).FIGURE 10. C/N0 (digital signal file playback mode).
Another Hardware/Software Option
We have also worked with the manufacturer of the LabSat hardware signal simulator to include some of the software functionality of our USRP system.
The LabSat GNSS simulator (see FIGURE 11) can be used to record live navigation satellite RF data streamed onto a hard drive. This can then be played back as an RF signal. When integrated with the SatGen software, simulated digitized RF data can be generated and played back into the LabSat simulator in place of the recorded, digitized GNSS RF signals.
FIGURE 11. LabSat GNSS simulator.
The core of the SatGen software is our Signal Architect software component, which has been adapted to run on the LabSat platform to allow simulation of the multiple GNSS satellite signals.
Hardware. The latest version of the LabSat hardware design (LabSat 2) enables the record and playback of GPS and GLONASS synchronized RF data streams (see FIGURE 12). When recording the GPS or GLONASS signals, the RF L1 channels (1575.42 MHz for GPS and 1602.0 MHz for GLONASS) are down-converted to a 0-Hz intermediate frequency. The signals are sampled (2 bit I and Q) at 16.368 MHz to capture the full GLONASS set of frequency channels. The GPS and GLONASS data is then interleaved into a 4-bit data stream and recorded in an internal buffer as a binary file. A high-speed USB link then transmits the data to a PC before streaming onto the PC hard disk. For playback, the PC streams the stored binary data to the LabSat via the USB link. The recorded digital GPS and GLONASS signals are up-converted onto the GPS and GLONASS RF channels and played back into the receiver under test. A digital attenuator on the output can adjust the RF output level.
FIGURE 12. LabSat GNSS simulator hardware design.
Using the LabSat record and playback mode, all of the real-world effects on the GNSS signals are recorded, including multipath effects, drop-outs, and atmospheric effects, allowing repeatable tests to be performed on GNSS receivers under a variety of real-world conditions, such as operating in urban canyons. This is ideal for debugging fault conditions on GNSS equipment and software. For more extensive simulations in different environments, the LabSat SatGen software can be used to generate simulated scenarios at any time or place or for a dynamic environment.
SatGen Scenario Simulation. SatGen is a software package that allows users to define trajectories for use in generating simulated data files for playback into LabSat. A user-defined trajectory file can be used to create a LabSat-simulated scenario for a route anywhere in the world. Routes can be generated directly from NMEA files imported directly into SatGen from a GPS datalogger or from user-defined routes generated using Google Earth.
SatGen users can use Google Earth to define a route by creating a path using its “Add Path” tool. The user can use as many or as few waypoints as the user wants, and can edit routes by moving, adding, or removing waypoints. The path is saved as a standard Google Earth KML file, which is imported into SatGen, which then fills in and smoothes the trajectory between the waypoints. The user can also define velocity profiles, or SatGen can provide these automatically. SatGen creates an NMEA file that is used to generate a binary I/Q simulated signal file for replay on the LabSat hardware.
Signal Architect Simulation. The core of the SatGen software is GNSS Signal Architect, an upgraded version of our GPS Signal Architect, which provides the capability to simulate multiple GPS signals and also different GNSS signals.
Signal Architect imports the NMEA trajectory either from a prerecorded file or from one generated using SatGen, and uses this file to generate a GNSS-simulated scenario. The user specifies the input GPS satellite constellation through a Yuma-format almanac file and the GLONASS constellation through a GLONASS almanac file in “.agl” or RINEX format. These files are then used to generate the simulated pseudorange, Doppler, and carrier phase for the GPS and GLONASS satellites in view of the simulated GNSS receivers above a specified mask angle. This simulated range data is then used to generate the digitized I/Q signals for the GPS and GLONASS satellites. Users who have access to our GNSS Signal Simulation Toolbox (an upgrade of our GPS toolbox) will have the added ability to modify the GNSS signal strength and add additional high-resolution error models to the simulated signals including multipath or GNSS signal error characteristics. The resulting I/Q simulated data file for the GPS plus GLONASS constellation is then recorded in a data file, which can be loaded into the LabSat hardware for playback into a receiver under test.
Test results using the LabSat and SatGen combination have demonstrated that highly accurate navigation solutions can be obtained with a variety of playback modes.
Conclusion
The combination of our GPS Signal Architect software with either the SCU and USRP or LabSat has proven to be an ideal low-cost GPS signal simulation tool with the capability of simulating or recording the complete GPS signal spectrum, including both the civil and the military codes for playback. The initial release of the GPS Signal Architect Test Set supports L1 operation and C/A- and P-code and M′ signal simulation or C/A- and P(Y)-code and M′ record and playback, while both GPS and GLONASS signal generation and playback is available with LabSat.
Our team of GPS and RF experts is continually developing and updating the system to provide additional functionality. Future releases of our test set will include support for multi-frequency SDR hardware and the capability to simulate other civil and military GPS signals, and also those of other global navigation satellite systems. To reflect this capability, we have branded the latest version of our simulation system, the GNSS Signal Architect Test Set.
Acknowledgments
The authors acknowledge the support of Ettus Research LLC in the development of the technology associated with the USRP system, as well as Racelogic Ltd. for collaboration on the LabSat GNSS simulator. USRP is a registered trademark of National Instruments Corp.
The article is based primarily on the papers “GPS Signal Simulation Using Open Source GPS Receiver Platform” presented at the Virginia Tech Symposium on Wireless Personal Communication in June 2011 and “SatGen GNSS Signal Simulation Software” presented at ION GNSS 2011 in Portland, Oregon, in September 2011.
Manufacturers
The GNSS Signal Architect Test Set was developed by Navsys Corp. The USRP used for the test set is the Ettus Research LLC model USRP N210. The LabSat 2 GNSS Simulator and associated SatGen software is produced by Racelogic Ltd. The GPS equipment used in our tests was a Novatel DL-4 plus receiver and a GPS-702GG antenna.
Alison Brown is the president and chief executive officer of Navsys Corp., Colorado Springs, Colorado, which she founded in 1986. Brown has a Ph.D. in mechanics, aerospace, and nuclear engineering from UCLA, an M.S. in aeronautics and astronautics from MIT, and an M.A. and B.A. in engineering from Cambridge University. She is a fellow of the Institute of Navigation and an honorary fellow of Sidney Sussex College, Cambridge.
Jarrett Redd is a senior systems engineer with Navsys Corp. working on hardware, firmware, and embedded systems development for signal acquisition, processing, and transmission. He holds an M.S. and B.S. in computer engineering from Texas A&M University.
Mark-Anthony Hutton is a software engineer with Navsys Corp. working on GNSS signal simulation tools and the GPS Jammer Detection and Location System. He holds a B.S. in computer science from the University of Colorado at Colorado Springs.
FURTHER READING
• Authors’ Proceedings Papers
“SatGen GNSS Signal Simulation Software” by A. K. Brown, M.-A. Hutton, M. Quigley, and M. Sampson in Proceedings of ION GNSS 2011, the 24th International Technical Meeting of the Satellite Division of The Institute of Navigation, Portland, Oregon, September 19–23, 2011, pp. 2031–2034.
“GPS M’-Code and P-Code Signal Simulation Using an Open Source Radio Platform” by A. Brown and B. Johnson in Proceedings of ION GNSS 2011, the 24th International Technical Meeting of the Satellite Division of The Institute of Navigation, Portland, Oregon, September 19–23, 2011, pp. 1494–1498.
“Modeling and Simulation of GPS Using Software Signal Generation and Digital Signal Reconstruction” by A. Brown, N. Gerein, and K. Taylor in Proceedings of the 2000 National Technical Meeting of The Institute of Navigation, Anaheim, California, January 26–28, 2000, pp. 646–652.
“GPS Simulation” by M. B. May in GPS World, Vol. 5, No. 10, October 1994, pp. 51–56.
• Matlab Simulation Toolboxes
“GPS MATLAB Toolbox Review” by A.K. Tetewsky and A. Soltz in GPS World, Vol. 9, No. 10, October 1998, pp. 50–56.
• NMEA 0183
NMEA 0183, The Standard for Interfacing Marine Electronic Devices, Ver. 4.00, published by the National Marine Electronics Association, Severna Park, Maryland, November 2008.
By Stéphane Gallot, Pascal Dutot, and Christophe Sajous
A new hardware assessment tool automates testing and mission replay, managing military GPS receiver input and output data, with an operational implementation and with a better control of initialization conditions, especially direct P(Y) acquisition. The test bench drives a GPS/Galileo simulator, a digital jammer, and software programs for visibility computation based on terrain modeling, and for multipath generation on 3D renderings.
Comprehensive assessment of military GPS receivers becomes more complex as they are integrated into advanced systems. To limit testing on systems under live conditions, laboratory evaluations with real elements are essential.
A new hybrid test bench called Statistical INERtial Gnss HYbrid in Simulation (SINERGHYS) is designed for governmental use to validate the integration of GPS/Galileo receivers within the navigation system for different platforms. As system-level requirements become more stringent, this bench has been designed to assess the behavior of the complete system in an operational context.
This new assessment hardware-in-the-loop tool is designed to automate testing and to replay missions with an operational implementation and with a better control of initialization conditions, especially direct P(Y) acquisition. This test bench drives many simulation tools: a GPS/Galileo simulator, a digital miniaturized jammer, and different softwares such as one enabling the computation of visibility depending on the terrain modeling, or one dedicated to the generation of multipaths on surfaces of realistic 3D scenes.
Figure 1. Depiction of SINERGHYS.Figure 2. Focus on the bench.
A Common Bench. Since 2000, with the arrival of the new cryptographic generation (the selective availability anti-spoofing module, or SAASM), the French government defence procurement agency (DGA) GPS laboratory decided to buy off-the-shelf GPS SAASM receivers that cover different form factors and applications. To test performance, it was necessary to acquire a test bench suitable for each GPS receiver. Testing procedures became more and more complex, and most of the manufacturer-provided benches could not perform every test required, such as direct P(Y) acquisition. To improve French expertise concerning GPS receivers, the DGA GPS laboratory decided to develop a common, generic test bench taking into account the integration constraints of each receiver. The perimeter of the hybrid test bench consists of a PC and a generic GPS test bench.
Figures 3 and 4 show examples of military GPS receivers integrated into the bench.
Figure 3. MPE-S (Ground-based application, Rockwell Collins).Figure 4. 1000S (Avionics,Thales).Figure 5. Embedded jammer.Figure 6. Jamming environment for a fighter aircraft. (Click to enlarge.)
Bench management is centralized, so test conditions are generic, and all simulation parameters are fully controlled. This enables users to display a unique view of the complete information and to be able to replay specific scenarios.
The bench manages military GPS receivers’ input and output data as described in the respective receivers’ interface control document (ICD) or interface specification: this enables, for example, the initialization of GPS receivers by sending precise time to facilitate direct P(Y) acquisition. This new bench is compatible with many GPS receivers with different form factors and applications.
Several receivers can be tested at the same time with the same software, so that the behavior of the GPS receivers can be compared in real time. Data from the different receivers can be observed on the same window of the graphic user interface (GUI). Specific data from ICDs can be displayed on the GUI. The user can visualize three different windows: the first is related to integrity, the second to alarms, and the third to cryptography. All the data output by the receivers can be recorded and replayed.
To facilitate and enhance trials on GPS receivers, the bench can use a Monte Carlo method, enabling sequentially and automatically chained scenarios, up to 10,000 test sequences, primarily for characterization of time-to-first-fix (TTFF).
Inertial navigation system (INS)/GPS hybridization in real time can be simulated via processing based on a Kalman filter of the information delivered by simulated INS and GPS. Loose and tight coupling can be selected through the GUI as well as filter parameters. The Kalman filter design is independent from the receiver and from the type of trajectory simulated. The user can decide whether the GPS receiver does receive aiding either from the simulated INS, or from the optimal navigation (output of Kalman filter).
Interfaces
The bench can interface with various external means and drive some tools and materials involved in the functioning of the bench.
With GPS Simulator. In the interface with the simulator, an intuitive GUI facilitates scenario preparation. When ready, SINERGHYS begins to drive the GPS simulator in remote-control mode. Any type of trajectory can be simulated with its operational environment modeled. The simulator outputs an RF signal to the receiver, and representative aiding, if required, by ethernet protocol to SINERGHYS.
With Jammer. Two types of interference signal generators can be used with the bench. Any available waveform can be generated. The bandwidth can go up to 20 Mhz for one generator and up to 80 Mhz for the other.
SINERGHYS is also compatible with a specific jammer called Embedded Jammer, designed to test vulnerability of GNSS systems (Figure 5).
The GPS receiver under test tracks the real GPS satellites combined with the simulated jamming signal. Thanks to the position and attitudes provided by the aircraft and to a modelized antenna diagram, the jammer computes in real time representative jamming that would be generated by real jammers.
This jammer works in two modes: localized mode (coordinates, jammer power, and waveform) and power profile mode. It was initially designed to be used inside an aircraft but can be used for laboratory testing as well.
The simulated environment is defined in the configuration software: waveform, emitter, scenario definitions (bands, number of emitters), and antenna diagram.
Four GNSS bands can be selected: GPS L1 and L2 (40 MHz) and Galileo E6 (40 MHz) and E5 (90 MHz). The embedded jammer can generate up to 14 simultaneous jammers per band, each with different waveforms. Therefore, up to 56 simultaneous jammers can be simulated.
The center frequency of the jamming signals can be chosen anywhere in the bandwidth. Modulation examples: continuous wave, broadband noise, binary phase shift keying), binary offset carrier (x,y), and so on.
Figure 7. Modulation examples.
External software interfaces fall under three categories.
Warfare. Electronic warfare software, which provides jamming coverage, performs a precise assessment of propagation (reflection and diffraction) of the interfering signals (depending on terrain modeling). Interference levels are transmitted to SINERGHYS during pre-processing.
Figure 8. Warfare GUI.
Satellite Tool Kit (STK). This software is designed to provide sophisticated modeling and visualization capabilities and performs functions critical to all mission types, including propagation of vehicles, and determination of visibility areas and times. STK generates paths for space and ground-based objects, such as satellites, ships, aircraft, and land vehicles. STK also provides animation capabilities and a two-dimensional map background for visualizing the path of these vehicles. Within SINERGHYS, STK is used for real-time visualization.
Figure 9. STK GUI.
Ergospace. This software is designed to generate multipaths, enabling the modeling of reflected paths of different satellite signals on surfaces of realistic 3D scenes. Pre-processed multipaths are sent to SINERGHYS and generated by the GPS simulator. The software is also used for real-time visualization.
Figure 10. Ergospace GUI.Figure 11. Example of the window showing the general state of the GPS receiver (c/n, svid, gram receiver and channel states, code and frequency tracked).
Operational Mission Characterization
The bench can evaluate and characterize receiver performance in most possible representative conditions.
Management of GPS Inputs/Outputs. Both black and red keys can be loaded inside the GPS receivers in both DS101 and DS102 protocols. This loading can be performed manually through key loaders such as KYK13 or DTD/ANCYZ10, but also through the host application with hexadecimal keys.
The bench can send commands to GPS receivers such as non-volatile memory erasure command, INS, precise time source, precise time and time interval (PTTI) activation commands, or choices between “mixed mode” and “all Y,” between “L1 primary” and “L2 primary,” and so on. Depending on user requirements, the bench can provide time, position, speed, almanac, ephemeris, or specific navigation sub-frames.
To test the jamming resistance of GPS receivers, it is essential to be able to provide INS aiding. SINERGHYS uses perfect or degraded aiding and adapts the format or the frequency for the considered GPS receiver.
Direct P(Y) acquisition functionality is an important case that needs to be evaluated. The GPS receiver needs a precise time to perform direct P(Y) acquisition. The time accuracy, from a few nanoseconds to several milliseconds, has a strong impact on the GPS behavior. A special delay box applied to the pulse-per-second signal of the GPS simulator in accordance with PTTI message (that is, time figure of merit), enables such a simulated accuracy.
A standard IS 153-like interface was developed to display GPS data on a convenient GUI in order to have a common software to visualize output data from the GPS receivers. The user can also visualize some specific data from GPS ICDs concerning integrity, alarms, and cryptography.
All receiver output data are recorded for later analysis.
Table 1. Example of Direct P(Y) acquisitions in accordance with time uncertainty (with times to get “GRAM state 5” and “protected status”).
Monte Carlo Trials
The bench enables sequentially and automatically chaining scenarios (up to 10 000 test sequences) to perform statistics on acquisition times. Indeed, it is primarily used for the characterization of TTFF. GPS signal acquisition is dependent on many different parameters, as described in Figure 12. To properly characterize receiver acquisition times requires a large number of tests. The comparison with GPS Receiver Applications Module requirements can be easily performed.
Figure 12. Setup parameters to study GPS signal acquisition.Figure 13. Example of a random selection for the position error.
One Monte Carlo trial consists of a repetition of unitary test: powering the receiver, then sending to the GPS receiver random errors of position, speed, time, levels of jamming, and finally stopping the test sequence on trigger. At the end of Monte Carlo trials, statistical computing enables accurate analysis and expertises.
The random selections are optimized to reduce the number of cases. The bench can replay a particular case: as the seeds are deterministic, a special case of Monte Carlo method can be selected and replayed.
Real-Time INS/GPS Data Fusion
The information delivered by INS and GPS are processed by a Kalman filter. The INS trajectory is provided by the simulator or by an external file.
Two types of coupling are considered: loose coupling with position and velocity information, and tight coupling with pseudoranges and delta ranges to estimate errors. In both cases, the GPS receiver receives aiding from either the simulated INS or the optimal navigation (Kalman filter output).
Figure 14. Example of an optimal navigation along a specified trajectory in a jamming environment.Figure 15. Position and velocity errors and navigation corridor.
The purpose of the Kalman filter is to estimate the navigation errors (position, velocity, and attitudes) and sensor errors (INS, GPS).
The filter design is original because it is independent from the receiver under test and from the type of application (hardiness privileged with reference to jamming). It is also able to estimate the time offset between position and velocity measurement on any GPS receiver under test.
Conclusion
SINERGHYS combines several resources into a single test bench. A complex mode can simulate an operational implementation with different interfaces and by chaining test sequences: receiver initialization, management of the switching of antenna patterns during a simulation, masking of GPS signals, management of jamming, INS/GPS data fusion, and so on. In this mode, missions can be replayed in a realistic environment. This bench is a complementary resource for flight trials and digital models because it can characterize the initialization phases with a good control of initial conditions. SINERGHYS enables users to know, as precisely as possible, the capabilities and limitations of a specific global navigation chain.
Manufacturers
SINERGHYS was developed by Bertin Technologies and specified by the French Ministry of Defense (MoD)DGA Information Superiority. It drives a Spirent GPS/Galileo simulator, Agilent 4431B and MXG generators, and software programs such as Analytical Graphics, Inc. (AGI) Satellite Tool Kit and Ergospace 3D scenes. The embedded jammer was developed by Ineo Defense in 2010 to MoD-DGA specifications.
Stéphane Gallot works at the French MoD (DGA Information Superiority) as a radionavigation expert. His particular interest is the integration of military GPS receivers including SAASM modules within French platforms.
Pascal Dutot is an architect engineer at the French MoD (DGA Information Superiority). His main activity is to optimize and control GPS integration in the global navigation chain.
Christophe Sajous works at the French MoD (DGA Information Superiority) as a radionavigation expert. He is also responsible for the “navigation per satellites” laboratory within the radionavigation department.
Taoglas is launching the AA.16X Dominator series of antennas, which have a wider bandwidth to cover the GLONASS operating frequencies up to 1610 MHz, a good axial ratio, and a double resonance design for optimum reception at the centre frequencies. The company will showcase its line of antennas at CTIA in New Orleans May 8-10.
Taoglas’ GPS antennas are being used in the field by many different M2M solution providers including tracking, telematics, and GPS manufacturers, the company said.
The AA.161 Dominator is a magnetic mount GPS-GLONASS IP67, external antenna incorporating a 35-millimeter ceramic patch. It is a wide-band active patch antenna product with a large integral ground that delivers a gain up to 35 dB. With the Dominator antenna series, Taoglas has a comprehensive range of GPS-GLONASS active embedded antennas (AGGP series) and passive embedded (CGGP) antennas for automotive first-tier TS16949 and after-market applications.
“In the coming months, for the first time the true availability of GPS and GLONASS satellites along with the latest generation of GNSS receivers are going to dramatically change the performance of M2M location devices,” said Ronan Quinlan, Director Taoglas. “With close to double the amount of satellites to draw from compared to a stand-alone GPS constellation, we are now going to see quicker time to first fixes with accuracy improving from meters to sub one meter. The ability to view and lock on four or more satellites in traditionally difficult reception areas such as urban canyons, city centers or locations with restricted views of the horizon, will give M2M manufacturers the ability to triangulate and pinpoint locations with greater accuracy and with quicker time to first fix.”
Taoglas’ new Dominator antennas have been rigorously tested and pre-approved by the GNNS receiver companies worldwide and have been shown to display higher and more consistent gain in comparison to competing antennas, the company claimed. Two key components have been engineered from scratch for the Dominator series, a wide-band front-end SAW filter (critical to prevent out of band noise entering on both GPS and GLONASS degrading the signal) and a high-gain 35-mm patch.
CAST Navigation of Tewksbury, Massachusetts introduced its SGX GPS Satellite Simulator. With its compact size — 7 × 11× 3 inches — and weighing in at just over 4 pounds, the SGX is CAST’s newest and smallest fully capable simulator to date.
The new SGX replaces the CAST-SIMCOM Simulator which was a 17-inch, 50-pound simulator. The SGX lightweight portability operates on AC or battery power, features 16 channels of L1 C/A and P codes, and is extremely accurate and repeatable, according to the company.
Features include touch screen, individual satellite power control, and start and stop scenarios with a touch of a button.
The CAST-SGX is portable, affordable, lightweight and utilizes CAST long standing proven technology.
CAST has been in the GPS simulation and support business for more than 25 years, designing, developing, manufacturing, and integrating innovative GPS/INS simulators and associated equipment for government, military, prime vendor, and consumer markets.
As result of a Cooperative Research and Development Agreement (CRADA) between the U.S. Coast Guard and UrsaNav, Inc., on-air tests are being conducted from the former Loran Support Unit site in New Jersey.
One of the CRADA’s goals is to research, evaluate, and document a wireless technical approach as an alternative to GPS for providing precise time. The ability to obtain precise time to at least one microsecond is necessary for the proper operation and functioning of many critical industries and systems. Examples include telecommunications networks, banking and finance, energy and power delivery, emergency services, transportation systems, and military and homeland security systems.
Additional on-air tests are planned at various sites throughout the United States. Broadcasts will test several different frequencies, waveforms, and modulation techniques using evolutionary, state-of-the-art technology. Reception of these broadcasts are planned at both on-shore and off-shore locations, and will include advanced LF data delivery techniques. The results of these trials will be presented at national and international conferences. Parties interested in any part of the trial, or interested in doing their own measurements, are invited to contact UrsaNav.
The company has partnered with precise-time synchronization company Symmetricom and Nautel, supplier of high-power RF transmitters. According to UrsaNav, this “alliance of expertise” provides the foundation technology for a wide-area, terrestrial-based alternative to satellite systems such as GPS, GLONASS, and Galileo.
“Global government, industry, and academic experts recognize that advanced LF signals, of which eLoran is just one example, can provide alternative timing — either as a stand-alone service, or as a component of an existing positioning, navigation, and timing (PNT) service. The high-power, virtually jam-proof and spoof-proof LF signals operate independently of GPS and GNSS, and provide a Universal Coordinated Time (UTC) time reference in the order of tens of nanoseconds. The recognition of the criticality of time to many aspects of our national critical infrastructure has led to establishment of the CRADA to evaluate the benefits of an LF wide-area timing system.”
The LF signals can also be used as pseudoranges mixed in with GPS, or if enough transmitters are available, as a fully independent PNT network. In other words, a true backup PNT capability for safety-of-life navigation, for dispatching first responders, and for supporting critical national infrastructures.
First Galileo PRS Signal Received
Septentrio and QinetiQ, in close partnership with the European Space Agency (ESA) and their industrial partners, achieved the first successful reception of the encrypted Galileo Public Regulated Service (PRS) signal from the first Galileo satellites, launched in November 2011.
The signal was received on the Galileo PRS Test User Receiver (PRS-TUR) jointly developed by Septentrio (Leuven, Belgium) and QinetiQ (Malvern, United Kingdom) under an ESA contract. For the reception test, the receiver was installed in the Galileo Control Centre in Fucino, Italy, and operated by technical experts from ESA.
Septentrio and QinetiQ are long-term contributors to the Galileo Programme, working closely with ESA, the European GNSS Agency (GSA), and European industrial partners since 2003.
Count Five Compass IGSOs
The BeiDou-2/Compass G5 satellite launched on February 24 has achieved an initial approximately geostationary orbit.
The current sub-satellite east longitude is 57.23 degrees. The intended final orbital slot may be 58.75 degrees, one of the previously announced orbital locations and one used by the BeiDou-1 demonstration system.
The 2012 NextGen Plan specifically mentions GPS/GNSS as follows:
Performance Based Navigation (PBN). The current aircraft fleet is well equipped with PBN capability. In the air carrier community, the heart of the PBN capability is the Flight Management System, which uses input from multiple distance measuring equipment (DME), or from the GNSS using a GPS sensor or a GPS with Wide Area Augmentation System (WAAS) sensor.
Ground Based Augmentation System Landing System (GLS) Enabler. This program researches use of differential GPS corrections to support Category III (Cat III) approaches. This capability will be the same as Cat III instrument landing system (ILS), without the need to restrict taxiing aircraft near antennas and at reduced cost to the FAA.
Automatic Dependent Surveillance–Broadcast (ADS-B). Aircraft position (long-lat, altitude, and time) is determined using GPS, an internal inertial navigational reference system or other navigation aids. ADS-B Out involves transmission of a GPS position (or of comparably performing navigation equipment meeting integrity and accuracy requirements) from an aircraft to display its location to controllers on the ground or to pilots in other aircraft equipped with ADS-B In.
Low-Visibility/Ceiling Approach.Localizer Performance (LP) with Vertical Guidance (LPV) Approaches. These are more cost-effective to implement compared to additional ground-based navigation aids (NAVAIDs) and their approach procedures. Increasing the number of LPV/LP approaches will provide further incentives for users to equip with GPS/WAAS. This will provide increased utility to the more than 40,000 general aviation aircraft that are already WAAS-capable. The FAA will also deliver LP approaches to runways that do not qualify for LPVs due to obstacles.
Ground Based Augmentation System (GBAS) Precision Approaches. GPS/GBAS support precision approaches to Cat I and eventually Cat II/III minima for properly equipped runways and aircraft. GBAS can support approach minima at airports with fewer restrictions to surface movement and offers potential for curved precision approaches. GBAS may also support high-integrity surface movement requirements.
— Bill Thompson, GPS World aviation editor
LightSquared-Sprint Contract Terminated
Business Case for GPS Threat Gone Away
The principal business prop under the LightSquared plan for ancillary terrestrial component (ATC) broadcast of a powerful signal that would have disrupted GPS operations dropped out from under the company on March 16, as wireless carrier Sprint terminated its $9 billion agreement with LightSquared. LightSquared had several such partnership agreements, but the Sprint deal was the largest, and in many eyes the driver of the aggressive plan. With it gone, LightSquared’s other deals will likely dissipate — and the current threat, at least, to GPS industry and users should effectively go away.
Sprint has apparently concluded that LightSquared has no prospect of reversing the revocation of its conditional waiver last month by the Federal Communications Commission, as a result of extensive testing conducted by the company, various government agencies, and the GPS industry. Earlier, Sprint had twice extended its tentative agreement with LightSquared as the tests took place over the last year, but reached the end of its road March 16 — which is also the last day the FCC is accepting public comments on its decision to revoke the waiver.
An official LightSquared statement said termination of the Sprint agreement was “in the best business interests of both companies, and was not unexpected given the regulatory delays.” Sprint will return $65 million in prepayments that LightSquared made to Sprint.
Some analysts have predicted that LightSquared may be forced to sell off its assets by the end of the year. Among these assets are the spectrum licenses for the lower LightSquared band (1526–1536 MHz), the so-called Low 10, and the higher band (1545-1555 MHz), known as the Upper 10, adjacent to GPS L1. These bands have a history of trading hands as their owners go into bankruptcy or otherwise out of business.
The next touchpoint of concern for the GPS community is the outcome or perhaps various outcomes of the FCC workshop on spectrum efficiency and receivers that took place March 12–13. The workshop was convened to discuss the characteristics of receivers and how their performance can affect the efficient use of spectrum and opportunities for the creation of new services, according to the FCC.
How Irregularities in Electron Density Perturb Satellite Navigation Systems
By the Satellite-Based Augmentation Systems Ionospheric Working Group
INNOVATION INSIGHTS by Richard Langley
THE IONOSPHERE. I first became aware of its existence when I was 14. I had received a shortwave radio kit for Christmas and after a couple of days of soldering and stringing a temporary antenna around my bedroom, joined the many other “geeks” of my generation in the fascinating (and educational) hobby of shortwave listening. I avidly read Popular Electronics and Electronics Illustrated to learn how shortwave broadcasting worked and even attempted to follow a course on radio-wave propagation offered by a hobbyist program on Radio Nederland. Later on, a graduate course in planetary atmospheres improved my understanding.
The propagation of shortwave (also known as high frequency or HF) signals depends on the ionosphere. Transmitted signals are refracted or bent as they experience the increasing density of the free electrons that make up the ionosphere. Effectively, the signals are “bounced” off the ionosphere to reach their destination.
At higher frequencies, such as those used by GPS and the other global navigation satellite systems (GNSS), radio signals pass through the ionosphere but the medium takes a toll. The principal effect is a delay in the arrival of the modulated component of the signal (from which pseudorange measurements are made) and an advance in the phase of the signal’s carrier (affecting the carrier-phase measurements). The spatial and temporal variability of the ionosphere is not predictable with much accuracy (especially when disturbed by space weather events), so neither is the delay/advance effect. However, the ionosphere is a dispersive medium, which means that by combining measurements on two transmitted GNSS satellite frequencies, the effect can be almost entirely removed. Similarly, a dual-frequency ground-based monitoring network can map the effect in real time and transmit accurate corrections to single-frequency GNSS users. This is the approach followed by the satellite-based augmentation systems such as the Federal Aviation Administration’s Wide Area Augmentation System.
But there is another ionospheric effect that can bedevil GNSS: scintillations. Scintillations are rapid fluctuations in the amplitude and phase of radio signals caused by small-scale irregularities in the ionosphere. When sufficiently strong, scintillations can result in the strength of a received signal dropping below the threshold required for acquisition or tracking or in causing problems for the receiver’s phase lock loop resulting in many cycle slips.
In this month’s column, the international Satellite-Based Augmentation Systems Ionospheric Working Group presents an abridged version of their recently completed white paper on the effect of ionospheric scintillations on GNSS and the associated augmentation systems.
The ionosphere is a highly variable and complex physical system. It is produced by ionizing radiation from the sun and controlled by chemical interactions and transport by diffusion and neutral wind. Generally, the region between 250 and 400 kilometers above the Earth’s surface, known as the F-region of the ionosphere, contains the greatest concentration of free electrons. At times, the F-region of the ionosphere becomes disturbed, and small-scale irregularities develop. When sufficiently intense, these irregularities scatter radio waves and generate rapid fluctuations (or scintillation) in the amplitude and phase of radio signals. Amplitude scintillation, or short-term fading, can be so severe that signal levels drop below a GPS receiver’s lock threshold, requiring the receiver to attempt reacquisition of the satellite signal. Phase scintillation, characterized by rapid carrier-phase changes, can produce cycle slips and sometimes challenge a receiver’s ability to hold lock on a signal. The impacts of scintillation cannot be mitigated by the same dual-frequency technique that is effective at mitigating the ionospheric delay. For these reasons, ionospheric scintillation is one of the most potentially significant threats for GPS and other global navigation satellite systems (GNSS).
Scintillation activity is most severe and frequent in and around the equatorial regions, particularly in the hours just after sunset. In high latitude regions, scintillation is frequent but less severe in magnitude than that of the equatorial regions. Scintillation is rarely experienced in the mid-latitude regions. However, it can limit dual-frequency GNSS operation during intense magnetic storm periods when the geophysical environment is temporarily altered and high latitude phenomena are extended into the mid-latitudes. To determine the impact of scintillation on GNSS systems, it is important to clearly understand the location, magnitude and frequency of occurrence of scintillation effects.
This article describes scintillation and illustrates its potential effects on GNSS. It is based on a white paper put together by the international Satellite-Based Augmentation Systems (SBAS) Ionospheric Working Group (see Further Reading).
Scintillation Phenomena
Fortunately, many of the important characteristics of scintillation are already well known.
Worldwide Characteristics. Many studies have shown that scintillation activity varies with operating frequency, geographic location, local time, season, magnetic activity, and the 11-year solar cycle. FIGURE 1 shows a map indicating how scintillation activity varies with geographic location. The Earth’s magnetic field has a major influence on the occurrence of scintillation and regions of the globe with similar scintillation characteristics are aligned with the magnetic poles and associated magnetic equator. The regions located approximately 15° north and south of the magnetic equator (shown in red) are referred to as the equatorial anomaly. These regions experience the most significant activity including deep signal fades that can cause a GNSS receiver to briefly lose track of one or more satellite signals. Less intense fades are experienced near the magnetic equator (shown as a narrow yellow band in between the two red bands) and also in regions immediately to the north and south of the anomaly regions. Scintillation is more intense in the anomaly regions than at the magnetic equator because of a special situation that occurs in the equatorial ionosphere. The combination of electric and magnetic fields about the Earth cause free electrons to be lifted vertically and then diffuse northward and southward. This action reduces the ionization directly over the magnetic equator and increases the ionization over the anomaly regions. The word “anomaly” signifies that although the sun shines above the equator, the ionization attains its maximum density away from the equator.
FIGURE 1. Global occurrence characteristics of scintillation. (Figure courtesy of P. Kintner)
Low-latitude scintillation is seasonally dependent and is limited to local nighttime hours. The high-latitude region can also encounter significant signal fades. Here scintillation may also accompany the more familiar ionospheric effect of the aurora borealis (or aurora australis near the southern magnetic pole) and also localized regions of enhanced ionization referred to as polar patches. The occurrence of scintillation at auroral latitudes is strongly dependent on geomagnetic activity levels, but can occur in all seasons and is not limited to local nighttime hours. In the mid-latitude regions, scintillation activity is rare, occurring only in response to extreme levels of ionospheric storms. During these periods, the active aurora expands both poleward and equatorward, exposing the mid-latitude region to scintillation activity. In all regions, increased solar activity amplifies scintillation frequency and intensity. Scintillation effects are also a function of operating frequency, with lower signal frequencies experiencing more significant scintillation effects.
Scintillation Activity. Scintillation may accompany ionospheric behavior that causes changes in the measured range between the receiver and the satellite. Such delay effects are not discussed in detail here but are well covered in the literature and in a previous white paper by our group (see Further Reading, available online).
Amplitude scintillation can create deep signal fades that interfere with a user’s ability to receive GNSS signals. During scintillation, the ionosphere does not absorb the signal. Instead, irregularities in the index of refraction scatter the signal in random directions about the principal propagation direction. As the signal continues to propagate down to the ground, small changes in the distance of propagation along the scattered ray paths cause the signal to interfere with itself, alternately attenuating or reinforcing the signal measured by the user. The average received power is unchanged, as brief, deep fades are followed by longer, shallower enhancements.
Phase scintillation describes rapid fluctuations in the observed carrier phase obtained from the receiver’s phase lock loop. These same irregularities can cause increased phase noise, cycle slips, and even loss of lock if the phase fluctuations are too rapid for the receiver to track.
Equatorial and Low Latitude Scintillations. As illustrated in Figure 1, the regions of greatest concern are the equatorial anomaly regions. In these regions, scintillation can occur abruptly after sunset, with rapid and deep fading lasting up to several hours. As the night progresses, scintillation may become more sporadic with intervals of shallow fading. FIGURE 2 illustrates the scintillation effect with an example of intense fading of the L1 and L2 GPS signals observed in 2002, near a peak of solar activity. The observations were made at Ascension Island located in the South Atlantic Ocean under a region that has exhibited some of the most intense scintillation activity worldwide. The receiver that collected this data was one that employs a semi-codeless technique to track the L2 signal. Scintillation was observed on both the L1 and L2 frequencies with 20 dB fading on L1 and nearly 60 dB on L2 (the actual level of L2 fading is subject to uncertainty due to the limitations of semi-codeless tracking). This level of fading caused the receiver to lose lock on this signal multiple times. Signal fluctuations depicted in red indicate data samples that failed internal quality control checks and were thereby excluded from the receiver’s calculation of position. The dilution of precision (DOP), which is a measure of how pseudorange errors translate to user position errors, increased each time this occurred. In addition to the increase in DOP, elevated ranging errors are observed along the individual satellite links during scintillation.
FIGURE 2. Fading of the L1 and L2 Signals from one GPS satellite recorded from Ascension Island on March 16, 2002. Absolute power levels are arbitrary. (Figure courtesy of C. Carrano)
FIGURE 3 illustrates the relationship between amplitude and phase scintillations, also using measurements from Ascension Island. As shown in the figure, the most rapid phase changes are typically associated with the deepest signal fades (as the signal descends into the noise). Labeled on these plots are various statistics of the scintillating GPS signal: S4 is the scintillation intensity index that measures the relative magnitude of amplitude fluctuations, τI is the intensity decorrelation time, which characterizes the rate of signal fading, and σφ is the phase scintillation index, which measures the magnitude of carrier-phase fluctuations.
FIGURE 3. Intensity (top) and phase scintillations (bottom) of the GPS L1 signal recorded from Ascension Island on March 12, 2002. (Figure courtesy of C. Carrano)
The ionospheric irregularities that cause scintillation vary greatly in spatial extent and drift with the background plasma at speeds of 50 to 150 meters per second. They are characterized by a patchy pattern as illustrated by the schematic shown in FIGURE 4. The patches of irregularities cause scintillation to start and stop several times per night, as the patches move through the ray paths of the individual GPS satellite signals. In the equatorial region, large-scale irregularity patches can be as large as several hundred kilometers in the east-west direction and many times that in the north-south direction. The large-scale irregularity patches contain small-scale irregularities, as small as 1 meter, which produce scintillation. Figure 4 is an illustration of how these structures can impact GNSS positioning. Large-scale structures, such as that shown traversed by the signal from PRN 14, can also cause significant variation in ionospheric delay and a loss of lock on a signal. Smaller structures, such as those shown traversed by PRNs 1, 21, and 6, are less likely to cause loss of the signal, but still can affect the integrity of the signal by producing ranging errors. Finally, due to the patchy nature of irregularity structures, PRNs 12 and 4 could remain unaffected as shown. Since GNSS navigation solutions require valid ranging measurements to at least four satellites, the loss of a sufficiently large number of satellite links has the potential to adversely affect system performance.
FIGURE 4. Schematic of the varying effects of scintillation on GPS.
FIGURE 5 illustrates the local time variation of scintillations. As can be seen, GPS scintillations generally occur shortly after sunset and may persist until just after local midnight. After midnight, the level of ionization in the ionosphere is generally too low to support scintillation at GNSS frequencies. This plot has been obtained by cumulating, then averaging, all scintillation events at one location over one year corresponding to low solar activity. For a high solar activity year, the same local time behavior is expected, with a higher level of scintillations.
FIGURE 5. Local time distribution of scintillation events from June 2006 to July 2007 (in 6 minute intervals). (Figure courtesy of Y. Béniguel)
FIGURE 6 (top panel) shows the variation of the monthly occurrence of scintillation during the pre-midnight hours at Ascension Island. The scintillation data was acquired by the use of Inmarsat geostationary satellite transmissions at 1537 MHz (near the GNSS L1 band). The scintillation occurrence is illustrated for three levels of signal fading, namely, > 20 dB (red), > 10 dB (yellow), and > 6 dB (green). The bottom panel shows the monthly sunspot number, which correlates with solar activity and indicates that the study was performed during the years 1991 to 2000, extending from the peak of solar cycle 22 to the peak of solar cycle 23. Note that there is an increase in scintillation activity during the solar maximum periods, and there exists a consistent seasonal variation that shows the presence of scintillation in all seasons except the May-July period. This seasonal pattern is observed from South American longitudes through Africa to the Near East. Contrary to this, in the Pacific sector, scintillations are observed in all seasons except the November-January period. Since the frequency of 1537 MHz is close to the L1 frequencies of GPS and other GNSS including GLONASS and Galileo, we may use Figure 6 to anticipate the variation of GNSS scintillation as a function of season and solar cycle. Indeed, in the equatorial region during the upcoming solar maximum period in 2012-2013, we should expect GNSS receivers to experience signal fades exceeding 20 dB, twenty percent of the time between sunset and midnight during the equinoctial periods.
FIGURE 6. Frequency of occurrence of scintillation fading depths at Ascension Island versus season and solar activity levels. (Figure courtesy of P. Doherty)
High Latitude Scintillation. At high latitudes, the ionosphere is controlled by complex processes arising from the interaction of the Earth’s magnetic field with the solar wind and the interplanetary magnetic field. The central polar region (higher than 75° magnetic latitude) is surrounded by a ring of increased ionospheric activity called the auroral oval. At night, energetic particles, trapped by magnetic field lines, are precipitated into the auroral oval and irregularities of electron density are formed that cause scintillation of satellite signals. A limited region in the dayside oval, centered closely around the direction to the sun, often receives irregular ionization from mid-latitudes. As such, scintillation of satellite signals is also encountered in the dayside oval, near this region called the cusp.
When the interplanetary magnetic field is aligned oppositely to the Earth’s magnetic field, ionization from the mid-latitude ionosphere enters the polar cap through the cusp and polar cap patches of enhanced ionization are formed. The polar cap patches develop irregularities as they convect from the dayside cusp through the polar cap to the night-side oval. During local winter, there is no solar radiation to ionize the atmosphere over the polar cap but the convected ionization from the mid-latitudes forms the polar ionosphere. The structured polar cap patches can cause intense satellite scintillation at very high and ultra-high frequencies. However, the ionization density at high latitudes is less than that in the equatorial region and, as such, GPS receivers, for example, encounter only about 10 dB scintillations in contrast to 20-30 dB scintillations in the equatorial region.
FIGURE 7 shows the seasonal and solar cycle variation of 244-MHz scintillations in the central polar cap at Thule, Greenland. The data was recorded from a satellite that could be viewed at high elevation angles from Thule. It shows that scintillation increases during the solar maximum period and that there is a consistent seasonal variation with minimum activity during the local summer when the presence of solar radiation for about 24 hours per day smoothes out the irregularities.
FIGURE 7. Variation of 244-MHz scintillations at Thule, Greenland with season and solar cycle. (Figure courtesy of P. Doherty)
The irregularities move at speeds up to ten times larger in the polar regions as compared to the equatorial region. This means that larger sized structures in the polar ionosphere can create phase scintillation and that the magnitude of the phase scintillation can be much stronger. Large and rapid phase variations at high latitudes will cause a Doppler frequency shift in the GNSS signals which may exceed the phase lock loop bandwidth, resulting in a loss of lock and an outage in GNSS receivers.
As an example, on the night of November 7–8, 2004, there was a very large auroral event, known as a substorm. This event resulted in very bright aurora and, coincident with a particularly intense auroral arc, there were several disruptions to GPS monitoring over the region of Northern Scandinavia. In addition to intermittent losses of lock on several GPS receivers and to phase scintillation, there was a significant amplitude scintillation event. This event has been shown to be very closely associated with particle ionization at around 100 kilometers altitude during an auroral arc event. While it is known that substorms are common events, further studies are still required to see whether other similar events are problematic for GNSS operations at high latitudes.
Scintillation Effects
We had mentioned earlier that the mid-latitude ionosphere is normally benign. However, during intense magnetic storms, the mid-latitude ionosphere can be strongly disturbed and satellite communication and GNSS navigation systems operating in this region can be very stressed. During such events, the auroral oval will extend towards the equator and the anomaly regions may extend towards the poles, extending the scintillation phenomena more typically associated with those regions into mid-latitudes.
An example of intense GPS scintillations measured at mid-latitudes (New York) is shown in FIGURE 8. This event was associated with the intense magnetic storm observed on September 26, 2001, during which the auroral region had expanded equatorward to encompass much of the continental U.S. This level of signal fading was sufficient to cause loss of lock on the L1 signal, which is relatively rare. The L2 signal can be much more susceptible to disruption due to scintillation during intense storms, both because the scintillation itself is stronger at lower frequencies and also because semi-codeless tracking techniques are less robust than direct correlation as previously mentioned.
FIGURE 8. GPS scintillations observed at a mid-latitude location between 00:00 and 02:00 UT during the intense magnetic storm of September 26, 2001. (Figure courtesy of B. Ledvina)
Effects of Scintillation on GNSS and SBAS
Ionospheric scintillation affects users of GNSS in three important ways: it can degrade the quantity and quality of the user measurements; it can degrade the quantity and quality of reference station measurements; and, in the case of SBAS, it can disrupt the communication from SBAS GEOs to user receivers. As already discussed, scintillation can briefly prevent signals from being received, disrupt continuous tracking of these signals, or worsen the quality of the measurements by increasing noise and/or causing rapid phase variations. Further, it can interfere with the reception of data from the satellites, potentially leading to loss of use of the signals for extended periods. The net effect is that the system and the user may have fewer measurements, and those that remain may have larger errors. The influence of these effects depends upon the severity of the scintillation, how many components are affected, and how many remain.
Effect on User Receivers. Ionospheric scintillation can lead to loss of the GPS signals or increased noise on the remaining ones. Typically, the fade of the signal is for much less than one second, but it may take several seconds afterwards before the receiver resumes tracking and using the signal in its position estimate. Outages also affect the receiver’s ability to smooth the range measurements to reduce noise. Using the carrier-phase measurements to smooth the code substantially reduces any noise introduced. When this smoothing is interrupted due to loss of lock caused by scintillation, or is performed with scintillating carrier-phase measurements, the range measurement error due to local multipath and thermal noise could be from three to 10 times larger. Additionally, scintillation adds high frequency fluctuations to the phase measurements further hampering noise reduction.
Most often scintillation will only affect one or two satellites causing occasional outages and some increase in noise. If many well-distributed signals are available to the user, then the loss of one or two will not significantly affect the user’s overall performance and operations can continue. If the user has poor satellite coverage at the outset, then even modest scintillation levels may cause an interruption to their operation. When scintillation is very strong, then many satellites could be affected significantly. Even if the user has excellent satellite coverage, severe scintillation could interrupt service. Severe amplitude scintillation is rarely encountered outside of equatorial regions, although phase effects can be sufficiently severe at high latitudes to cause widespread losses of lock.
Effect on Reference Stations. The SBAS reference stations consist of redundant GPS receivers at precisely surveyed locations. SBAS receivers need to track two frequencies in order to separate out ionospheric effects from other error sources. Currently these receivers use the GPS L1 C/A-code signal and apply semi-codeless techniques to track the L2 P(Y) signal. Semi-codeless tracking is not as robust as either L1 C/A or future civil L5 tracking. The L2 tracking loops require a much narrower bandwidth and are heavily aided with scaled-phase information from the L1 C/A tracking loops. The net effect is that L2 tracking is much more vulnerable to phase scintillation than L1 C/A, although, because of the very narrow bandwidth, L2 tracking may be less susceptible to amplitude scintillation. Because weaker phase scintillation is more common than stronger amplitude scintillation, the L2 signal will be lost more often than L1. The SBAS reference stations must have both L1 and L2 measurements in order to generate the corrections and confidence levels that are broadcast. Severe scintillation affecting a reference station could effectively prevent several, or even all, of its measurements from contributing to the overall generation of corrections and confidences. Access to the L5 signal will reduce this vulnerability. The codes are fully available, the signal structure design is more robust, and the broadcast power is increased. L5-capable receivers will suffer fewer outages than the current L2 semi-codeless ones, however strong amplitude scintillation will still cause disruptions. Strong phase scintillation may as well.
If scintillation only affects a few satellites at a single reference station, the net impact on user performance will likely be small and regional. However, if multiple reference stations are affected by scintillation simultaneously, there could be significant and widespread impact.
Effect on Satellite Datalinks. The satellites not only provide ranging information, but also data. When scintillation causes the loss of a signal it also can cause the loss or corruption of the data bits.
Each GPS satellite broadcasts its own ephemeris information, so the loss of data on an individual satellite affects only that satellite. A greater concern is the SBAS data transmissions on GEOs. This data stream contains required information for all satellites in view including required integrity information. If the data is corrupted, all signals may be affected and loss of positioning becomes much more likely.
Mitigation Techniques. There are several actions that SBAS service providers can take to lessen the impact of scintillation. Increasing the margin of performance is chief among them. The more satellites a user has before the onset of scintillations, the more likely he will retain performance during a scintillation event. In addition, having more satellites means that a user can tolerate more noise on their measurements. Therefore, incorporating as many satellites as possible is an effective means of mitigation. GNSS constellations in addition to GPS are being developed. Including their signals into the user position solution would extend the sky coverage and improve the performance under scintillation conditions. (See the white paper for other mitigation techniques.)
Conclusions and Further Work
Ionospheric scintillations are by now a well-known phenomenon in the GNSS user community. In equatorial regions, ionospheric scintillations are a daily feature during solar maximum years. In auroral regions, ionospheric scintillations are not strongly linked to time of the day. In the mid-latitude regions, scintillations tend to be linked to ionospheric disturbances where strong total electron content gradients can be observed (ionospheric storms, strong traveling ionospheric disturbances, solar eclipses, and so on).
While the global climatic models of ionospheric scintillations can be considered satisfactory for predicting (on a statistical basis) the occurrence and intensity of scintillations, the validation of these models is suffering from the fact that at very intense levels of scintillation, even specially designed scintillation receivers are losing lock. Also, the development of models that can predict reliably the size of scintillation cells (regions of equal scintillation intensity), which allows establishing joint probabilities of losing more than one satellite simultaneously, is still ongoing.
The data presented in Figure 2 was produced by an Ashtech, now Ashtech S.A.S. Z-XII GPS receiver. The data presented in Figure 5 was obtained from Javad, now Javad GNSS and Topcon Legacy GPS receivers and GPS Silicon Valley, now NovAtel GSV4004 GPS scintillation receivers. The data presented in Figure 8 was obtained from a non-commercial receiver.
The Satellite-Based Augmentation Systems Ionospheric Working Group was formed in 1999 by scientists and engineers involved with the development of the Satellite Based Augmentation Systems in an effort to better understand the effects of the ionosphere on the systems and to identify mitigation strategies. The group now consists of over 40 members worldwide.
The scintillation white paper was principally developed by Bertram Arbesser-Rastburg, Yannick Béniguel, Charles Carrano, Patricia Doherty, Bakry El-Arini, and Todd Walter with the assistance of other members of the working group.
“Morphology of Phase and Intensity Scintillations in the Auroral Oval and Polar Cap” by S. Basu, S. Basu, E. MacKenzie, and H. E. Whitney in Radio Science, Vol. 20, No. 3, May–June 1985, pp. 347–356, doi: 10.1029/RS020i003p00347.
“Global Morphology of Ionospheric Scintillations” by J. Aarons in Proceedings of the IEEE, Vol. 70, No. 4, April 1982, pp. 360–378, doi: 10.1109/PROC.1982.12314.
“Equatorial Scintillation – A Review” by S. Basu and S. Basu in Journal of Atmospheric and Terrestrial Physics, Vol. 43, No. 5/6, pp. 473–489, 1981, doi: 10.1016/0021-9169(81)90110-0.
• Effects of Scintillations on GNSS
“GNSS and Ionospheric Scintillation: How to Survive the Next Solar Maximum by P. Kintner, Jr., T. Humphreys, and J. Hinks in Inside GNSS, Vol. 4, No. 4, July/August 2009, pp. 22–30.
“Analysis of Scintillation Recorded During the PRIS Measurement Campaign” by Y. Béniguel, J.-P. Adam, N. Jakowski, T. Noack, V. Wilken, J.-J. Valette, M. Cueto, A. Bourdillon, P. Lassudrie-Duchesne, and B. Arbesser-Rastburg in Radio Science, Vol. 44, RS0A30, 11 pp., 2009, doi:10.1029/2008RS004090.
“Characteristics of Deep GPS Signal Fading Due to Ionospheric Scintillation for Aviation Receiver Design” by J. Seo, T. Walter, T.-Y. Chiou, and P. Enge in Radio Science, Vol. 44, RS0A16, 2009, doi: 10.1029/2008RS004077.
“GPS and Ionospheric Scintillations” by P. Kintner, B. Ledvina, and E. de Paula in Space Weather, Vol. 5, S09003, 2007, doi: 10.1029/2006SW000260.
“Space Weather Effects of October–November 2003” by P. Doherty, A. Coster, and W. Murtagh in GPS Solutions, Vol. 8, No. 4, pp. 267–271, 2004, doi: 10.1007/s10291-004-0109-3.
“First Observations of Intense GPS L1 Amplitude Scintillations at Midlatitude” by B. Ledvina, J. Makela, and P. Kintner in Geophysical Research Letters, Vol. 29, No. 14, 1659, 2002, doi: 10.1029/2002GL014770.
• Previous “Innovation” Articles on Space Weather and GNSS
The National Geodetic Survey (NGS) has issued a “Kinematic GPS Challenge” to the community in support of NGS’ airborne gravity data collection program, called Gravity for the Redefinition of the American Vertical Datum (GRAV-D). The “Challenge” is meant to provide a unique benchmarking opportunity for the kinematic GPS community by making available two flights of data from GRAV-D’s airborne program for their processing. By comparing the gravity products that are derived from a wide variety of kinematic GPS processing products, a unique quality assessment is possible.
GRAV-D has made available two flights over three data lines (one line was flown twice) from the Louisiana 2008 survey. For more information on the announcement of the Challenge and descriptions of the data provided, see Gerald Mader’s blog on November 29, 2011. The GRAV-D program routinely operates at long-baselines (up to 600 km), high altitudes (20,000 to 35,000 ft), and high speeds (up to 280 knots), a challenging data set from a GPS perspective. As of December 2011, ten groups of kinematic GPS processors have provided a total of sixteen position solutions for each flight. At two data lines per flight, this yielded 64 total position solutions. Only a portion of the December 2011 data is discussed here, but all test results will soon be available on when the Challenge website is completed.
Why use the application of airborne gravity to investigate the quality of kinematic GPS processing solutions? Because the gravity measurement itself is an acceleration, which is being recorded with a sensor on a moving platform, inside a moving aircraft, in a rotating reference frame (the Earth). The gravity results are completely reliant on our ability to calculate the motion of the aircraft— position, velocity, and acceleration. These values are used in several corrections that must be applied to the raw gravimeter measurement in order to recover a gravity value (Table 1). The corrections in Table 1 are simplified to assume that the GPS antenna and gravimeter sensor are co-located horizontally and offset vertically by a constant, known distance.
Table 1. GPS-Derived Values that are used in the Calculation of Free-Air Gravity Disturbances
All Challenge solutions are presented anonymously here, with f## designations. For each flight of data, the software that made the f01 solution is the same as for f16, f02 the same as f17, and so on.
Test #1: Are the solutions precise and accurate?
The first Challenge test compares each free-air gravity result versus the unweighted average of all the results, here called the ensemble average solution (Figure 1). This comparison highlights any GPS solutions whose gravity result is significantly different from the others, and will group together solutions that are similar to each other (precise). Precision is easy to test this way, but in order to tell which gravity results are accurate calculations of the gravity field, a “truth” solution is necessary. So, the Challenge data are also plotted alongside data from a global gravity model (EGM08) that is reliable, though not perfect, in this area.
Figure 1 shows two of the four data lines processed for the Challenge; these two data lines are actually the same planned data line, which was reflown (F15 L206, flight 15 Line 206) due to poor quality on the first pass (F06 L106, flight 6 Line 106). The 5-10 mGal amplitude spikes of medium frequency along L106 are due to turbulence experienced by the aircraft, turbulence that the GPS and gravity processing could not remove from the gravity signal.
Figure 1.
Figure 2.
Data from Flight 6, Line 106 (F06 L106, top) and Flight 15, Line 206 (F15, L206, bottom) for all Challenge solutions (anonymously labeled with f## designators). Figures 1 and 2. Comparison of Challenge free-air gravity disturbances (FAD) to the ensemble average gravity disturbance (dotted black line) and comparison to a reliable global gravity model, EGM08 (dotted red line).
Figure 3.
Figure 4.
Figures 3 and 4. Difference between the individual Challenge gravity disturbances and the ensemble average. The thin black lines mark the 2-standard deviation levels for the differences. For F15 L206, one solution (f23) was removed from the difference plot and statistics because it was an outlier. For both lines, the ensemble’s difference with EGM08 is not plotted because it is too large to fit easily on the plot.
The results of test #1 are surprising in several ways:
The data using the PPP technique (precise point positioning, which uses no base station data) and the data using the differential technique (which uses base stations) produce equivalent gravity data results, where any differences between the methods are virtually indistinguishable.
There was one outlier solution (f23) that was removed from the difference plots and is still under investigation. Also, on F15 L206, solution f28 had an unusually large difference from the average though it performed predictably on the other lines. Of the remaining solutions, four solutions stand out as the most different from all the others: f03/f18, f04/f19, f05/f20, and f07/f22.
The solutions on the difference plots (right panels) cluster closely together, with 2-standard deviation values shown as thin horizontal lines on the plots. The Challenge solutions meet the precision requirements for the GRAV-D program: +/- 1 mGal for 2-standard deviations.
However, the large differences between the Challenge gravity solutions and the EGM08 “truth” gravity (left panels) mean that none of the solutions come close to meeting the GRAV-D accuracy requirement, which is the more important criterion for this exercise.
Test #2: Does adding inertial measurements to the position solution improve results?
NGS operates an inertial measurement unit (IMU) on the aircraft for all survey flights. The IMU records the aircraft’s orientation (pitch, roll, yaw, and heading). Including the orientation information in the calculation of the position solution should yield a better position solution than GPS-only calculations, but it was not expected to be significantly better. Figure 2 shows the NGS best loosely-coupled GPS/IMU free-air gravity result versus the Challenge GPS-only results and Table 2 shows the related statistics.
Figure 5.
Figure 6.
Figures 5 and 6. F06 L105. (Figure 5) Comparison of Challenge FAD gravity solutions (ensemble=black dotted line) with EGM08 (red dotted line); (Figure 6) comparison of Challenge gravity solutions (all GPS-only; ensemble=black dotted line) with NGS’ coupled GPS/IMU gravity solution (red dotted line).
Table 2. Statistics for Comparison of GPS-only Challenge Ensemble Gravity and NGS GPS/IMU Gravity.
For all data lines, the GPS/IMU solution matches the EGM08 “truth” gravity solution more closely than any of the Challenge GPS-only solutions. In fact, the more motion that is experienced by the aircraft, the more that adding IMU information improves the solution. One conclusion from this test is that IMU data coupled with GPS data is a requirement, not optional, in order to obtain the best free-air gravity solutions.
Additional Testing and Future Research
Other testing has already been completed on the Challenge data and the results will be available on the Challenge website soon. Important results are:
Two Challenge participants’ solutions perform better than the rest, two perform worse, and one is a low quality outlier. The reasons for these differences are still under investigation.
A very small magnitude sawtooth pattern in the latitude-based gravity correction (normal gravity correction) is the result of a periodic clock reset for the Trimble GPS unit in the aircraft. This clock reset is uncorrected in the majority of Challenge solutions. The clock reset causes an instantaneous small change in apparent position, which results in a 1-2 mGal magnitude unreal spike in the gravity tilt correction at each epoch with a clock reset.
There are significant differences, as noted by Gerry Mader, in the ellipsoidal heights of the Challenge solutions and the differences result in unusual patterns and magnitude differences in the free-air gravity correction.
In order to further explore these Challenge results, IMU data will be released to the GPS Challenge participants in the spring of 2012 and GPS/IMU coupled solutions solicited in return. Additionally, basic information about the Challenge participants’ software and calculation methodologies will be collected and will form the basis of the benchmarking study.
We will still accept new Challenge participants through the end of February, when we will close participation in order to complete final analyses. Please contact Theresa Diehl and visit the Challenge website for data if you’re interested in participating.
As a result of a Cooperative Research and Development Agreement (CRADA) between the U.S. Coast Guard and UrsaNav, Inc., on-air tests are being conducted from the former Loran Support Unit site in New Jersey.
One of the CRADA’s goals is to research, evaluate, and document a wireless technical approach as an alternative to GPS for providing precise time. The ability to obtain precise time to at least one microsecond is necessary for the proper operation and functioning of many critical industries and systems. Examples include telecommunications networks, banking and finance, energy and power delivery, emergency services, transportation systems, and military and homeland security systems.
Additional on-air tests are planned at various sites throughout the United States. Broadcasts will test several different frequencies, waveforms, and modulation techniques using evolutionary, state-of-the-art technology. Reception of these broadcasts are planned at both on-shore and off-shore locations, and will include advanced LF data delivery techniques. The results of these trials will be presented at national and international conferences. Any party interested in any part of the trial, or interested in doing their own measurements, are invited to contact us.
UrsaNav provides advanced solutions for Low Frequency Alternative Positioning, Navigation, Timing, and Data, including high-performance eLoran Timing Receivers. The company has partnered with precise-time synchronization company Symmetricom and Nautel, supplier of high-power RF transmitters. According to UrsaNav, this “alliance of expertise” provides the foundation technology for a wide-area, terrestrial-based alternative to satellite systems such as GPS, GLONASS, and Galileo.
“We conclude that LightSquared’s proposed mobile broadband network will impact GPS services and that there is no practical way to mitigate the potential interference at this time.” These words from Lawrence Strickling, U.S. assistant secretary for communications and information and head of the National Telecommunications and Information Administration (NTIA), appear to signal the end of LightSquared’s run.
Strickling’s letter to Federal Communications Commission (FCC) chairman Julius Genachowski appeared in public on February 14. Later that same day, FCC spokesperson Tammy Sun released a statement from that agency that “the Commission will not lift the prohibition on LightSquared,” and that it plans to “vacate the Conditional Waiver Order, and suspend indefinitely LightSquared’s Ancillary Terrestrial Component authority.”
The NTIA and the FCC share responsibility for controlling U.S. radio spectrum use. The FCC supposedly has final authority in these matters, although the NTIA, representing government interests, may swing the bigger cat in the room. LightSquared’s inability to satisfy the requirements of the Federal Aviation Administration (FAA), coupled with unremitting frowning and glowering from the Department of Defense, may have been the deciding factors — more so than the uproar among most GPS manufacturers. The FAA and the U.S. military, two key government entities with widely fielded GPS equipment and applications, constituted the backbone that the NTIA finally showed, although the military has been, with one notable exception, silent on the issue, and indeed is not mentioned in the NTIA letter.
Strickling’s eight-page letter recaps the history, with a July 6, 2011, early climax: “Test results demonstrated that LightSquared’s then-planned deployment of terrestrial operations posed a significant potential for harmful interference to GPS services.” He relates further NTIA testing of cellular GPS receivers, joint continued analysis by FAA and LightSquared of impact on aviation receivers, and testing of general/personal navigation GPS receivers by the Executive Steering Group of the Interagency National Executive Committee for Space-Based Positioning, Navigation, and Timing (EXCOM).
Strickling quotes a January 13 letter from Ashton Carter, deputy secretary for defense, and John Porcari, deputy secretary for transportation: “It is the unanimous conclusion of the test findings by the EXCOM agencies that both LightSquared’s original and modified plans for its proposed mobile network would cause harmful interference to many GPS receivers. Additionally, an analysis by the FAA has concluded that the LightSquared proposals are not compatible with several GPS-dependent aircraft safety-of-flight systems. . . There appear to be no practical solutions or mitigations that would permit the LightSquared broadband service, as prosposed, to operate in the next few months or years without significantly interfering with GPS. As a result, no additional testing is warranted at this time.”
But Wait. We’re not done yet. Strickling calls for GPS receiver standards to be developed, citing the EXCOM’s decision that “federal agencies will move forward this year to develop and establish new GPS spectrum interference standards that will help inform future proposals for non-space commercial uses in the bands adjacent to the GPS signals.”
NTIA and PNT EXCOM will devise “standards for the development and procurement of GPS receivers to support their various mission requirements.” NTIA recognized “the importance that receiver standards could play as part of a forward-looking model for spectrum management even beyond the immediate issue of GPS.”
The FCC, in its concurrence statement to the NTIA letter, begins by reciting the mantras of “economic growth, job creation, and to promote competition . . . freeing up spectrum for mobile broadband,” and gradually works its way around to its decision on the waiver. This signals an ongoing commitment to make further efforts towards broadband implementation.
In-Car Nav Under Safety Scrutiny
The U.S. National Highway Traffic Safety Administration (NHTSA) proposed voluntary guidelines for car manufacturers on February 16, including a recommendation to design dashboards so that distracting devices are automatically disabled unless the vehicle is stopped and the transmission is in park. The agency is concerned about proliferation of text messages, GPS images, phone calls, and web surfing, and wants carmakers to curb those distractions when vehicles are moving.
Technological advances, among them GPS-enabled navigation, have raised concerns that drivers’ attention is being diverted too much from the road.
“We recognize that vehicle manufacturers want to build vehicles that include the tools and conveniences expected by today’s American drivers,” said NHTSA Administrator David Strickland. “The guidelines would offer real-world guidance to automakers to help them develop electronic devices that provide features consumers want without disrupting a driver’s attention or sacrificing safety.”
Under the guidelines, GPS and other navigation devices that provide directions would be permitted while driving, but NHTSA asks that they be designed so that drivers can’t manually enter a destination unless the car is in park. A spokesperson for the Alliance of Automobile Manufacturers cautioned against this. “There are often passengers in the car who can enter addresses, so we need to consider that when looking at requiring these technologies to only be used in park,” she said. “And if the GPS is disabled when moving, consumers can always bring their own Garmin into the vehicle. It’s complicated.”
Other dashboard technologies recommended for automatic disabling include text-messaging, Internet browsing, social media browsing, phone dialing and computer screen messages of 30 characters or more that are unrelated to driving.
Manufacturers are also urged to revise in-car designs to reduce to two seconds or less the amount of time drivers must divert their eyes from the road to use a device. Devices should also be designed so that drivers don’t have to use more than one hand or glance through extraneous information.
A spokesperson for state highway safety offices said that “the safest thing is for drivers not to use these systems at all — both hands on the wheel and the mind focused solely on driving.”
The process for writing actual federal rules often takes years to complete. The guidelines represent a way “ to continue the drumbeat” that distracted driving is a serious safety issue that costs lives.
NHTSA is also considering guidelines to address portable electronic devices drivers carry with them into cars, including GPS navigation systems.
SSTL-OHB to Build Eight More Galileo Satellites
European Commission Vice President Antonio Tajani announced in London that the consortium led by OHB System AG and Surrey Satellite Technology Ltd. (SSTL) will build a further eight satellites for the European Union’s Galileo satellite navigation program under the supervision of the European Space Agency.
The new contract will see SSTL, builder of the GIOVE-A satellite, continuing its role as payload prime, assembling, integrating, and testing the navigation payloads in the UK, while OHB System, as the prime contractor, builds the eight satellite platforms and executes final integration of all the satellites in Germany. The SSTL-OHB partnership is already building 14 satellites for the Galileo program and will draw on its heritage and experience to produce the additional satellites to demanding schedules.
SSTL is assembling the Galileo program payloads at its recently opened purpose-built Kepler technical facility in Guildford, UK. SSTL will manufacture the electrical harnesses and the electronics to interface the navigation payload with the satellite platform.
The remaining payload equipment will be externally procured by SSTL from European and other suppliers. SSTL’s payload solution is based on European-sourced atomic clocks, navigation signal generators, high-power traveling-wave tube amplifiers, and antennas, and will provide all of Galileo’s services.
Compass Poised
As this magazine goes to press, a new GNSS satellite may simultaneously be rising. The Chinese government issued a Notice to Airmen (NOTAM) for a satellite launch on, February 24, at about 16:20 UTC. According to web reports, the launch from the Xichang Satellite Launch Center will orbit the fifth geostationary satellite in the BeiDou-2/Compass constellation.
Funding Affirms NextGen; Unmanned Flight Advances Also
For the last five years, the Federal Aviation Adminstration (FAA) has made do with 23 short-term funding appropriations from Congress, but on January 30, congressional leaders agreed on a four-year, $63 billion funding bill. The funding will accelerate the creation of the NextGen (Next Generation Air Transportation System) air traffic control system. A new post will be created — the Chief NextGen Officer — to oversee the effort, and a schedule for progress will be set.
A key piece of NextGen includes GPS-enabled Required Navigation Performance (RNP), which allows an aircraft to fly a specific path between two 3-dimensionally defined points in space.
The bill also assures funding subsidies for rural airports at $190 million a year. New labor rules will make it harder for airline employees to unionize, requiring half the workers in a bargaining unit to petition for a vote to certify a union, an increase from the current 35 percent.
“All of us at this table made compromises,” Sen. Jay Rockefeller, D-W.Va., chair of the Senate’s transportation committee, told USA Today. “The outcome is that we have a bill that will take steps to modernize our air traffic control system, make the air transportation system safer than ever, and make certain small communities have access to critical air service.”
Unmanned Aircraft. Congress also passed legislation starting the clock on a number of deadlines the FAA must meet to safely integrate unmanned aircraft systems (UAS) into the national airspace system. Chief among them is a deadline for full integration by September 2015.
Using GPS to underlie the whole concept, the UAS industry has made significant technological advancements during the last decade, and the legislation recognizes the important role UAS will play in the future air transportation system.
Michael Toscano, president of the Association for Unmanned Vehicle Systems International (AUVSI) said, “UAS are truly a revolutionary-type technology, and I’m confident that once people can fly UAS in the national airspace for civil and commercial purposes, such as oil and pipeline monitoring, crop dusting, and search and rescue, a whole new industry will emerge, inventing products and accomplishing tasks we haven’t even thought of yet.”
Other major provisions of the bill include:
Requiring six UAS test sites within six months (similar to the language in the already-passed Defense Authorization bill);
Requiring small UAS (under 55 pounds) be allowed to fly in the U.S. Arctic, 24-hours-a-day, beyond line-of-sight, at an altitude of at least 2,000 feet, within one year;
Requiring expedited access for public users, such as law enforcement, firefighters, emergency responders;
Allowing first responders to fly very small UAS (4.4 pounds or less) within 90 days if they meet certain requirements.
The goal is to grant law enforcement and firefighters immediate access to start flying small systems to save lives and increase public safety.
Spectrum Swamp
On January 30, the same day that a LightSquared VP told an Institute of Navigation audience that moving to a different spectrum posed formidable difficulties, a company working on behalf of LightSquared contacted a Department of Defense official to discuss just such a spectrum swap.
The McChrystal Group, led by retired four-star general Stanley McChrystal, contacted the Department of Defense’s Mid-Atlantic Area Frequency Coordinator at Pawtuxet River, Maryland, to discuss “a spectrum swap.” The McChrystal representatives indicated interest in the upper 10 MHz (1515–1525 MHz) of the Aeronautical Mobile Telemetry band (1435–1525 MHz). This spectrum is vital to the development and test of aircraft and weapon systems, for both government agencies and industry, is heavily scheduled and utilized, and is also used for safety of life services (see “Letters to the Editor” in this issue, page 8).
Moving LightSquared’s license to a different radio frequency spectrum has been suggested by some as a possible exit strategy from the LightSquared/GPS interference conflict. At least one wireless industry analyst has surmised that this constituted a part of LightSquared’s strategic plan all along.
A source familiar with the situation contacted GPS World after this story appeared online to say that “a swap would be complicated but never ‘insurmountable.’ The bottom line is that [LightSquared’s VP] did not talk about swaps of any specific spectrum. He talked about the difficulty to get a wireless company up and running, and if you’ve got something that has spectrum, technology, and a successful business model, then that’s very rare, and you can’t necessarily duplicate it. But he said nothing about whether a swap of some specific kind of spectrum could be done. If the parties are willing, it’s actually not that hard.”
Nevada OKs Unmanned Driving
Nevada became the first state in the nation to authorize the use of autonomous vehicles on its roadways.
Manufacturers are developing vehicles that could allow a motorist to plug in a destination and let the vehicle drive there automatically. Google has several prototypes, logging more than 160,000 test miles.
The Nevada Department of Motor Vehicles will formalize licensing procedures for companies that want to test their vehicles in the state.
General Motors has run several tests, some in conjunction with Carnegie-Mellon University on a self-driving Chevrolet Tahoe, The Boss. BMW has several test vehicles in operation, as does Audi in collaboration with Stanford University. Many of these cars, or their predecessors, have participated in DARPA Grand Challenges, reported in this magazine.
SVN-49 Broadcasting on L-Band
GPS satellite SVN-49 began transmitting an L-band signal on or about February 2. SVN-49 is currently being used as a vehicle of opportunity for satellite subsystem testing. However, SVN-49 is declared unusable until further notice, and will not be included in the broadcast almanac.
By Hans-Georg Büsing, Ulrich Haak, and Peter Hecker
Future safety-relevant driver assistant systems demand vehicle state estimations accurate enough to match the position within a road lane, which cannot be provided by standalone GPS. A promising approach to meet the requirements is the fusion of standalone or differential GNSS measurements with vehicle sensor data like odometers or accelerometers. To achieve deeper sensor integration, a software GNSS receiver was developed at the Institute of Flight Guidance (IFF) that is able to use dead reckoning sensors to support its signal acquisition. This article presents an approach to estimate the signal states during outages based on the tightly coupled vehicle state, which reduces the reacquisition time and significantly increases the signal availability.
GNSS-based navigation is a key enabler for future advanced driver assistance systems (ADAS). Car manufacturers have identified automotive assistance systems as core devices to propose their uniqueness mainly in the luxury and upper-class market segments. While the precision and availability of loosely coupled single-frequency GPS navigation satisfies the requirements of typical route guidance systems, future automotive systems — especially those that enhance driving safety — are more demanding on positioning system performance.
The Institute of Flight Guidance (IFF) of the Technische Universität, Braunschweig, Germany, is involved in two research projects evaluating the performance of unaided traditional GNSS receivers coupled with vehicle sensor measurements such as odometers in a tightly coupled architecture. Besides these involvements, the IFF has developed a general-purpose software-based GNSS receiver allowing full access to signal processing routines.
The benefits of the tight sensor fusion are reliable state estimations even during total signal outages that are common in the automotive sector due to tunnels, parking decks, or urban canyons. In this architecture, the GNSS receiver works autonomously to deliver raw GNSS-measurements only. Additional knowledge provided by the vehicle sensors cannot be used to support the receiver in any way. Besides other beneficial aspects in the tracking channels, additional external knowledge about the vehicle state has the potential to reduce acquisition times and improve the measurement availability significantly.
The Institute of Flight Guidance uses a software environment called “Automotive Data and Time-Triggered Framework” (ADTF) for research in the field of ADAS and automotive navigation. In this software framework, the overall system architecture is assembled with independent modules. These modules are implemented as libraries and loaded into ADTF. Data is exchanged via pins that are defined as public variables. The framework also attaches timestamps to the individual measurements and adds a data recording and playback functionality.
From a general-purpose software GNSS receiver, presented at the ION GNSS 2010, we have derived an automotive-specific ADTF software receiver module. The software framework adds the flexibility to synchronously process measurements from vehicle sensors additionally to the IF data from the front end. This gives us the opportunity to aid signal processing in the software GNSS receiver with additional external sensors.
For positioning, a tightly coupled positioning filter based on GPS raw data measurements and the rear-wheel odometers is implemented. The vehicle’s motion is modeled using a kinematic relationship between the vehicle sensors and the GNSS measurements.
Based on the tightly coupled vehicle state estimation, an acquisition state is processed during signal outages that enables the software GNSS receiver to reacquire the satellite signal instantaneously with high precision.
In this article, the constituent parts of the system are presented and the estimation of the acquisition state derived. The system was tested in an urban scenario, and the state estimations validated with the recorded measurements.
System Architecture
The software-defined GNSS receiver developed by the IFF was designed to process the computationally expensive signal correlation on an Nvidia graphics board using the vast parallel processing capability of graphics processing units (GPUs). With the use of common graphics boards, an entire receiver can be implemented on an ordinary PC, needing only a front-end to receive digital GNSS signals in an intermediate frequency (IF) band.
For research in the field of vehicle state estimation, a derivate of the software receiver of the Institute of Flight Guidance has been implemented in the “Automotive Data and Time-Triggered Framework” (ADTF). The software is commonly used in the automotive industry for the development of ADAS. Figure 1 shows a typical system layout in ADTF. A central component of the framework is the ability to record and play back measurement data, which is indicated by the buttons on the left of the screenshot.
Figure 1. System Architecture in ADTF. (Click to enlarge.)
Within ADTF, the systems are assembled from modules that are shown as blocks within the graphical configuration editor. Standard modules such as the connection of common hardware are provided with the framework. Custom modules can be implemented in C++ by the user. Every module is implemented as a dynamic library (DLL) and interpreted by the framework. Modules can be featured with input and output pins.
These pins are implemented by using specific data types from the framework. The communication and data exchange between the modules is handled via these pins. They can be connected by graphically drawing connector lines in the configuration editor.
ADTF provides the user with classes for timing and threading. Processes can thereby be linked to the ADTF system time, which is especially important as the data replay can be slowed down or sped up for debugging.
The instantaneous reacquisition algorithm is based on a traditional approach of tightly coupling GNSS raw data with vehicle sensor measurements. The fusion is based on a kinematic model following the Ackermann geometry establishing the relationship between the vehicle’s motion and the respective measurements.
At each time step of an arriving measurement, the vehicle’s motion is predicted based on the last estimated state with an extended Kalman filter. The prediction is then corrected using either measurements from the vehicle sensors or GNSS raw measurements. The range and Doppler measurements are calculated in the tracking channels of the ADTF software GNSS receiver. The corrected vehicle state is then fed back into the kinematic model for the next update cycle.
In case the GNSS signal is lost in a tracking channel, a virtual tracking channel is initialized with the last calculated channel states. The change in the channel output is then predicted utilizing the change in the vehicle state and the current evaluation of the ephemeris. The schematic implementation of the channel state prediction is shown in Figure 2.
Figure 2. Schematic of Channel State Prediction. (Click to enlarge.)
Signal State Estimation
Using the tightly coupled architecture presented above, an estimated position and velocity can even be provided during total signal outages. Assuming that the last valid observation of a satellite signal is stored together with its respective time to and position, an estimation of the signal state (that is, Doppler frequency, code- and carrier-phase) based on the estimation of the vehicle state during the signal outage at time t1 can be used for an instantaneous signal reacquisition. Using the ephemeris data provided by the respective GPS satellite the range between a user position xu and the satellite xsv can be calculated using the following terms (1)
and (2)
with |…| indicating the Euclidian distance.
Therefore the change of the range can be obtained with equations (1) and (2): (3)
Assuming an unbiased Gaussian error distribution of the measurements, the tightly coupled system provides an estimation of the covariance matrix of the vehicle state. Using only the submatrix (4)
related to the vehicle position, the covariance of the user position along the line-of-sight to the satellite can be obtained with the Euclidean norm of the line-of-sight vector (5)
and the law of error propagation: (6)
Furthermore, using the law of error propagation, it can be shown that the variance of the change of range estimation in equation (3) is obtained by: (7)
With the last valid range measurement related to time to, the signal state at time t1 can be obtained for the pseudo-range PSR (8)
and the carrier phase Φ: (9)
The resulting variance of these estimations can by expressed by (10)
and (11)
respectively. The estimate of the Doppler and the related variance can be obtained analogous.
Considering the variances of the estimation, it can be decided if the signal can be reacquired instantaneously or if the receiver has to find the signal using standard acquisition routines in a limited search space.
Experimental Validation
The Volkswagen Passat station wagon operated by the Institute of Flight Guidance was used to evaluate the performance of the proposed algorithm (see PHOTO.) The test vehicle is customized from the standard by adding an additional generator to meet the power requirements of the measurement and processing hardware. In addition, the Controller Area Network (CAN) is mirrored and open to access the data collected by the sensors of the vehicle. The relevant sensors include a longitudinal accelerometer, a gyro for measuring the yaw rate as well as the odometers of all four wheels. The test vehicle is equipped with a GNSS front-end developed by the Fraunhofer Institute for Integrated Circuits. It is capable of streaming L1, L2, and L5 RF samples via two USB ports. The sampling rate of L1 is 40.96 MHz at an intermediate frequency of 12.82 MHz.
Test Vehicle. A customized Volkswagen Passat was used to evaluate performance of the algorithm.
The vehicle sensor data is streamed via CAN to an automotive PC from Spectra. It is equipped with an Intel quadcore CPU, 8 GB RAM, a Vector PCI CAN device and 256 GB SATA solid state disk allowing up to 195 MB/s writing speed. Additionally, it has been equipped with an Nvidia GeForce GT 440 graphics board that is used for processing the GNSS RF data. This specific graphics board was chosen because it offers a comparably high performance of the GPU at relatively low power consumption.
Both GNSS RF data and data from the vehicle sensor network are streamed to an ADTF hard disk recorder. Due to the setup of the data acquisition, several challenges have to be solved. The first challenge is that the front-end needs to be used as hardware-in-the-loop. It is by itself not equipped with an automated gain control. Therefore, it is not possible to just stream the RF data but it has to be decoded, processed for adjusting the gain, and then stored to the hard drive.
Secondly, the recording setup needs to cover high data rates. The GNSS front-end streams approximately 20 MB/s. As the data needs to be decoded and processed for gain control, the expanded data rate for recording is ~40 MB/s. In total including vehicle sensor measurements, >2000 data packets per second are streamed to the recorder. Because this could not be done using mechanical hard drives, we used solid state disks that also allow data storage during times of high vibration.
Related to the before-mentioned challenges, an efficient thread management needed to be implemented. The software framework’s threading classes are utilized to parallelize the receiver processes. Additionally, it has arisen that a significant part of the processing time is taken by the data transfer to the memory of the GPU.
In order to prove the advantages of an odometer-aided reacquisition, an applicable testing scenario was chosen. To distinguish an odometer-based aquisition approach from a model-based approach, a trajectory was chosen that features a right turn of 90 degrees immediately after cutting off the GNSS signal. A model-based kinematic prediction would project the trajectory in the direction of the latest known heading derived by the GNSS solution. Only a sensor-based state estimation is able to resolve the right turn. The driven trajectory is shown in Figure 3.
The GNSS signal has been cut off for approximately 10 seconds, which is equivalent of a 75-meter drive on dead reckoning sensors only after the right turn.
Figure 3. Trajectory of test drive includes a 90-degree turn. (Click to enlarge.)
Results
The following plots in Figure 4 show the performance of the virtual tracking channels. The plots in the upper row show the pseudorange output over time. For vividness they have been corrected for the motion of the respective satellite that is dominant due to their high speeds. Over a short period of time the satellites’ motion relative to the receiver can be linearly approximated. The pseudorange measurements over time were fit using a linear regression. The respective value of the linear regression was then subtracted from the pseudorange and plot over time as shown in the figures in the second row, leaving only the approximated influence of the vehicle’s motion.
Figure 4. Modified pseudorange and Doppler results of the virtual tracking channels. (Click to enlarge.)
The Doppler measurements have been similarly compensated by just subtracting the minimum measurement. These modifications of the pseudorange and Doppler measurements allow a direct comparison of each other as the Doppler can be understood as the first derivate of the pseudorange over time.
The results of PRN 6 show that the Doppler estimate during the GPS outage smoothly fits into the surrounding measurements without any major outliers. The plot of the pseudorange shows a similar behavior. The pseudorange could have potentially been modeled using a dynamic prediction that is not based on vehicle sensors due to the limited dynamics on the pseudorange measurements.
The Doppler plot of PRN 16 shows a strong change in the relative velocity between satellite and receiver. If a further projection of the Doppler using a linear dynamic model would have been used instead of predicting with vehicle sensors, it would likely have misled the reacquisition by ~ 50 Hz. The trend in the pseudorange measurements is comparable to PRN 6 at a higher rate of change.
The plots of PRN 21 probably show the advantages of using vehicle sensors for reacquisition best as the dynamics on pseudorange and Doppler are the most significant in the group. Both pseudorange and Doppler show a turning point during the GNSS outage. Especially, the pseudorange would have been mismodeled using a kinematic predicion that is not relying on additional sensors.
Conclusion
In this article, a tightly coupled positioning system implemented in the automotive-specific framework ADTF was presented that is based on the fusion of standard automotive sensor data and software receiver measurements. We showed that, using the tightly coupled solution, an acquisition state during signal outages can be estimated that allows the tracking channels to reacquire the signal instantaneously without the need of computationally expensive acquisition routines.
Under the assumption of a tightly coupled RTK position and small outage times, a reacquisition of the carrier phase without loosing the information about the phase ambiguity seems possible.
In the next version of the automotive GNSS receiver, the authors are planning to integrate the vehicle sensors to aid the tracking loops, which is likely to further improve tracking continuity especially in scenarios with high vegetation. Additionally, we plan to show that the implementation is capable of working in real time. Improvements of the initialization of the virtual tracking loops are also intended.
Acknowledgments
This article is based on a paper presented at ION-GNSS 2011, held September 19–23 in Portland, Oregon.
This work was funded by the Federal State of Lower Saxony, Germany. Project: Galileo – Laboratory for the research airport Braunschweig.
The authors would like to thank their colleagues working in the automotive navigation group for continuous support with the ADTF framework.
Hans-Georg Büsing holds a Dipl.-Ing. in aerospace engineering from the Technische Universität Braunschweig and has been a research engineer at IFF since 2008. He works in the area of applied satellite navigation, especially in the field of vehicle positioning.
Ulrich Haak holds a Dipl.-Ing. in mechanical engineering from the Technische Universität Braunschweig and joined IFF in 2008 as a research engineer. He works in the areas of receiver design and positioning algorithms.
Peter Hecker joined IFF in 1989 as research scientist. Initial focus of his scientific work was in the field of automated situation assessment for flight guidance. From 2000 until 2005, he was head of the DLR Pilot Assistance department. Since April 2005, he has been director of IFF. He is managing research activities in the areas of air/ground cooperative air traffic management, airborne measurement technologies and services, satellite navigation, human factors in aviation, and safety in air transport systems.
As a result of a Cooperative Research and Development Agreement (CRADA) between the U.S. Coast Guard and UrsaNav, Inc., on-air tests are being conducted from the former Loran Support Unit site in New Jersey.
