The European Commission (EC) has published an updated Galileo Open Service Signal-In-Space Interface Control Document (OS SIS ICD) giving technical specifications and performance expectations for the future system.
As reported by GPS World in October 2009, the EC will not charge for manufacturing licenses. No fees will be required for manufacturers to design, develop, make, or sell receivers capable of using the Galileo Open Service signal. Manufacturers are required to apply for the free licenses, which “will be provided on a non-discriminatory basis in accordance with European Union rules and international commitments.”
To obtain a license, interested parties must e-mail to [email protected], “mentioning their request for a license agreement, which is without any exclusivity or geographical limitation.”
In a section addressing intellectual property rights (IPR), previously the stumbling block towards free-market manufacture and sale of Galileo receivers, the release states that “The information contained in the OS SIS ICD . . . is subject to IPR. The use of [this] information . . . including the spreading codes which are subject to IPR, is hereby allowed for research and development and/or standardisation purposes . . . “ and, in a later section regarding commercial use, “. . . is hereby allowed for manufacturing, distribution, commercialisation, sale of electronic devices (e.g. chipsets and receivers) and supply of Value Added Services.”
Galileo Frequency Plan.
SBAS Woes
In mid-April, Intelsat announced it had lost control of its Galaxy 15 satellite that hosts the WAAS SBAS transponder used by the U.S. Federal Aviation Administration (FAA). Shortly thereafter, the FAA announced that the satellite, one of two used by WAAS, would drift out of usable orbit within two to four weeks.
Once G-15 is out of usable orbit, WAAS will be disrupted for users in northwest Alaska. The rest of the WAAS service area — U.S., Canada, Mexico — will operate normally but will be reduced to a single point of failure with one WAAS broadcasting satellite remaining (PRN 138).
The FAA is investigating at least two alternatives:
Utilize Inmarsat 3 (POR) that was previously used by WAAS before switching to Galaxy 15 in 2006. POR is located at 178°E.
Accelerate the testing of Inmarsat 4-F3 (PRN 133). Testing is already in progress and due to be complete in December 2010. The FAA stated that there is “potential to implement as an emergency release.”
Neither solution is an immediate one. The FAA stated that integrating POR back into operational WAAS would take 12–16 months. The quickest solution is to accelerate the implementation of PRN 133; the FAA said it might be able to shave 1–2 months from original target date.
The FAA stated that with only a single WAAS GEO broadcasting satellite, users may experience a temporary loss of service 3-5 times this year for up to five minutes each while WAAS Uplink Station Switchovers occur.
GAGAN Tumbles. A rocket carrying a satellite-based augmentation system (SBAS) satellite crashed into the Bay of Bengal, deaing a significant blow to India’s GPS-Aided Geo Augmented Navigation (GAGAN) program. The rocket was to deliver the two-ton GSAT-4, which hosted, among other things, an L-band transponder that was to broadcast GPS navigation corrections used by civil aviation and other transportation modes. GAGAN, a program that is years into development, is similar to and compatible with the U.S. WAAS, Europe’s EGNOS, and Japan’s MSAS, designed for next-generation international aviation navigation.
The initiative was using an Indian-designed and -built cryogenic engine on a rocket for the first time. The Hindu News website reported that “India began developing the cryogenic engine as its answer to technology denial regime as the U.S. not only refused the technology but also put pressure on Russia to backtrack on its commitment to New Delhi.”
The original GPS signals, and indeed most GPS signals including L5, utilize conventional pseudonoise (PN) signal code division multiple access (CDMA), some with both in-phase and quadrature-phase modulation. In the late 1990s, I generalized Manchester PN symbol-spreading by defining split-spectrum binary square wave symbol-spreading, in a series of limited-distribution papers for the Air Force GPS Independent Review Team (IRT). These split-spectrum signals have been developed and analyzed much more fully by many others, and they are now termed binary offset carrier (BOC) modulation. The BOC codes can provide a noise-error advantage by placing more of their spectral energy at an offset frequency, thereby increasing the Gabor bandwidth. They can also provide spectral separation from other GNSS signals in the same frequency band, for example, L1.
Efficient GPS/GNSS satellite power amplification dictates constant envelope signaling. After power amplification, however, signals are generally filtered by a cavity or other filter before broadcast through the antenna. In some instances, the cavity filter has an RF bandwidth of 24 MHz or 30 MHz. Receiver filtering removes out-of-band noise interference and permits signal-sampling rate reduction.
Objectives
Our first objective is to analyze performance of an assisted quasi-coherent delay-lock loop (QCDLL), a differentially coherent tracking receiver that employs the same discriminator channel as the optimal coherent DLL for noise and multipath performance advantages.
The second objective is to generalize the BOC symbol-spreading codes by employing other families of well-known finite-length codes and spreading techniques, and to compute some measures of their multipath and noise performance and spectral-shaping capabilities. We focus on general filtered binary coded symbol (BCS) signals using time-multiplexed Walsh codes that have potential advantages for multipath performance, along with more general spectral control. They may have applications for future GNSS signals and pseudolite transmitters where multipath is a serious concern. Time- or other multiplexed versions can perhaps be useful in permitting legacy signals to operate while upgrading to new signals with perhaps different and longer PN sequences.
QCDLL
Optimal digital communications signal processing in Gaussian noise employs a matched filter or correlator where the reference is the waveform itself. In contrast, for optimal tracking of small changes in signal time-delay, key information content is carried, not by the waveform itself, but by the changes in the waveform with time, that is, the time derivative. Focus on the changes in the waveform is consistent with my original 1961 paper on the delay lock loop (DLL), which showed that the optimum tracking estimator uses a delay discriminator reference signal that is the differentiated signal. The derivation of the maximum likelihood estimator of delay for small delay error in Gaussian noise is not repeated here, but we note that the Taylor’s series expansion of a differentiable baseband signal p[t] received with delay T+e delay for sufficiently small e after acquisition at estimate T is
We track various PN and BCS PN carrier modulated signals using an aided QCDLL. The QCDLL operates on a PN or other coherently modulated carrier. The QCDLL has two channels.
The upper channel in Figure 1 is the punctual autocorrelation carrier channel, where the received signal is correlated with the reference waveform, p[t+e], the PN waveform itself with delay error e. The punctual channel is also used for initial acquisition and data recovery. It provides both a reference carrier, data, and autocorrelation weighting for the lower discriminator channel. If there is no data modulation, the bandpass filters can be made more narrow. Also note that the QCDLL can operate on multiple I/Q or other multiplexed BCS signal by using composite reference codes.
FIGURE 1. Simplified quasi-coherent delay-lock loop (QCDLL) block diagram. The number-controlled oscillator (NCO) generates a continuous phase sine wave.
The lower channel is the delay error discriminator carrier channel where the reference, p’[t1e], is the time derivative of the PN signal p with the same delay error e. The filters in both channels have matched group delay and assisted digital tunable narrow-band filters for noise and Doppler removal. Thus, this QCDLL is a special type of assisted-GPS receiver that receives Doppler information from an external communications link. Both channels can also be assisted by an inertial measurement unit (IMU), for example a MEMS device, to estimate velocities (Doppler offset) and further reduce the tracking-filter bandwidth. The filtered product of the two carrier channels is termed the discriminator output, and it provides an estimate of the delay error. By multiplying the discriminator channel with the punctual channel, the discriminator output versus time error is narrowed in width while maintaining the sharp slope versus delay error, as well as removing carrier and data.
The QCDLL is the generalization of the Costas loop, just as the DLL is the generalization of the phase lock loop (PLL); for example, if p is a sine wave, then p’ is a cosine wave. For a trapezoidal signal waveform, the QCDLL has been shown to produce a similar but not identical output to a non-coherent DLL.
In Figure 1, the upper bandpass filter recovers the punctual channel, and the lower channel is the discriminator channel. The product of the two removes the carrier and data, and provides a delay error cross-correlation-autocorrelation product, the discriminator output.
Figure 2 shows an example PN trapezoidal waveform and its derivative as a simple example of a filtered PN pulse punctual channel reference and the differentiated filtered pulse as the discriminator channel reference. It can easily be shown that the discriminator channel (not the discriminator output) is equivalent to an early-late DLL with a early-late separation equal to the rise time of the trapezoidal pulse. Figure 3 shows the discriminator channel and output.
FIGURE 2. Trapezoidal PN (1 Mcps) waveform pulse and its time derivative with a 0.1-microsecond rise time.
FIGURE 3. Discriminator channel, d[e], and (bottom) discriminator output, R[e] Rd[e], for the 1.0 Mcps PN with the optimum 0.1-microsecond reference and the 0.1-microsecond rise-time trapezoidal waveform.For comparison, Figure 4 shows the step response of a 4-pole Butterworth filter with a 12-MHz bandwidth and its derivative. We also show a two-step approximation to this analog step response, which can be used to optimize a weighted multiple early-late DLL or multiple correlator approximation to the QCDLL.
FIGURE 4. Step amplitude response and slope for a 4-pole Butterworth filter with a 3-dB bandwidth of 12 MHz (one-sided). The time derivative of this step response is shown on the lower plot along with a rectangular approximation.
Although not proven, the QCDLL appears to have several advantages in both noise and multipath performance as compared to the more conventional early-late gate (that I first presented in 1963):
The QCDLL discriminator channel reference is the differentiated pulse. Although for the trapezoidal pulse waveform, the conventional early-late DLL can in effect use the same discrimiantor reference if the early-late separation is set equal to the rise-time, for more general filtered waveforms, the early-late DLL can only approximate the optimal reference. Properly weighted multiple early-late DLLs offer a better approximation as shown in Figure 4, but still only an approximation.
The QCDLL discriminator output of Figure 3 is the product of the correlator channel and the discriminator channel. When tracking precisely, the correlator channel output is at its peak correlation. In contrast, a noncoherent early-late DLL only produces correlator outputs that are by definition early and late. Thus neither of these is at their peak, and the noise performance suffers accordingly. By the same token, the noncoherent early-late DLL discriminator output must be wider than that of the QCDLL, and the QCDLL multipath performance is improved in the same manner.
From a computational point of view, the early-late DLL is computing the small difference between two large numbers, namely the small difference between the ealy and late correlator channels. In contrast, the QCDLL is only computing the correlation of the received waveform with the narrow differentiated waveform used as the discriminator reference. For the simple example of the trapezoidal PN waveform, this reference is simply a narrrow time gate of width equal to the rise time.
Generalized BCS Techniques
My 2010 ION ITM paper, upon which this article is based, discusses a number of generalized symbol coding techniques including Neuman-Hofman, Barker, and Generalized Multiphase Barker, each of which provides minimal autocorrelation sidelobes. Various chirp-coded symbols with linear variation in chip-rate with time are analyzed and provide reduced sidelobes and spectral shaping. Rademacher and Walsh codes, time-multiplexed and properly weighted, form further generalizations. These can be time- or IQ-multiplexed, and the time-multiplexing can in turn be pseudorandomly permuted. In the limited space of this article we only discuss time-multiplexed (TM) Walsh Code symbols.
TM Walsh Codes. Walsh functions form a complete orthonormal set of binary functions of dimension 2n. Walsh codes are generated as products of Rademacher codes. There are 2n Walsh function of 2n binary elements. Thus a weighted sum of Walsh functions can approximate any discrete-time, time-limited waveform. Each PN symbol is coded with a Walsh code. Then time-multiplex two or more different Walsh-coded symbols in a sequential or time-weighted manner. We can then tailor the autocorrelation function and its sidelobes and spectra by using selected members of this set and appropriate weighting. The resulting combined autocorrelation function is then the sum or weighted sum of the individual autocorrelation functions, since we assume independence of the PN chips. The 8-dimensional binary Walsh codes (Walsh order) are the rows in the matrix:
Figure 5 shows the trapezoidal filtered version of Walsh 7 for the dimension-8 Walsh functions.
FIGURE 5. Finite rise time trapezoidal Walsh coded symbol for Walsh code 7 with rise-time 0.03 microseconds and 1 Mcps.
Each Walsh sequence time multiplex modulates a separate and independent pseudorandom PN chip in sets of PN chips beginning from a PN epoch time; for example, the defined beginning of the PN sequence. Note that the equally weighted sum of all 8 Walsh functions is the vector {8,0,0,0,0,0,0,0}, which is equivalent to a single high-amplitude pulse of narrow width. Thus if we sum all of the Walsh functions, we obtain the equivalent of a single narrowband pulse where the autocorrelation sidelobes disappear. Even with filtering of the spreading waveform, the sidelobes can still be small. Likewise, the equally weighted sum of codes 5,6,7,8 is {4,4,0,0,0,0,0,0}, the Manchester code.
Since the Walsh functions form a complete orthonormal set, a weighted sum of Walsh functions can approximate any finite-duration signal of the same dimension, just as the Fourier series can approximate any periodic function. Thus a weighted sum of the Walsh functions in TM fashion can tailor the signal power spectral densities and autocorrelation functions to closely match a desired realizable function. Weighted TM BOC signals and Rademacher codes can also create useful approximations, but are not as general since they are not a complete orthonormal set.
The spectrum and autocorrelation functions of the individual Walsh functions vary markedly from one another. Figure 6 shows two different selections of Walsh functions to illustrate an example of spectral separation. The wider-frequency spectra signal is a TM of Walsh codes 5, 6, 7, 8 and has improved autocorrelation with lower sidelobes compared to a single BOC signal. The lower-frequency spectrum represents the 0 Walsh, which is conventional PN.
FIGURE 6. Shaped power spectra for two TM trapezoidal Walsh signals.Blue solid curve Walsh 1, dashed curve TM Wash 5,6,7,8.
Figure 7 shows the multipath error envelope of the TM Walsh spreading waveform for TM of all 8 codes in comparison, with TM of 5,6,7,8 in the presence of multipath amplitude 0.5 versus multipath delay. These results for TM of all 8 Walsh correspond closely to that of PN waveform of 8 Mcps and rise time of 0.03 ❍s as expected.
FIGURE 7. Envelope of the multipath delay error when using the Walsh spreading function of dimension 8 and a trapezoidal signal rise time of 0.03 microseconds.
The envelope of the error increases as one would expect, to approximately 0.03-microsecond multipath delay. The solid blue curve is the result where all TM 8 Walsh codes are used. The dashed curve is for the TM 5,6,7,8 used to generate the spectral separation shown in Figure 6.
We can permute TM of Walsh functions and transmit each of these permutations in a pseudorandom sequence. There are 8! 5 40,320 different permutations of 8 Walsh functions. Thus we can use a different arrangement of the 40,320 patterns every 8 PN chips and do so with a different PN sequence to prevent a jammer from time-synchronizing the jammer spectrum to the Walsh multiplexing spectra with time. Weighted time-multiplexing can also be augmented with I/Q multiplexing. Pseudorandom permutation of the Walsh codes can also diminish spectral lines of the basic PN sequence if the two PN sequences are relatively prime.
Conclusions
This discussion first examines the QCDLL and its performance for conventional PN signals, and then generalizes the family of symbol coding/spreading techniques. The BOC signal, first called the split-spectrum signal, has a limited but important ability to shape the spectrum. It also increases its Gabor bandwidth and corresponding noise performance as indicated by the Cramer-Rao bound. However, the BOC signal has large autocorrelation sidelobes that when operating on both sidelobes simultaneously can cause limitations. There are BOC receivers which avoid that issue by operating separately on upper and lower frequency components. However, our focus is on more
general symbol-coding techniques that reduce autocorrelation sidelobes and provide good multipath performance.
The assisted QCDLL may improve performance as compared to the more conventional early-late non-coherent DLL in at least these respects:
The non-coherent early-late DLL autocorrelation is by definition offset by D/2 in the early–late DLL when locked rather than a perfect punctual channel.
The conventional early-late reference is not equal to the differentiated signal except for a trapezoidal signal with rise time of D/2.
The QCDLL uses an optimal reference for the discriminator channel.
The discriminator output of the QCDLL is the product of the punctual channel correlator with the discriminator channel, and thus has a narrower width than that of an early-late DLL and c better multipath performance.
The early-late DLL computes the small difference between two large correlator outputs, whereas the QCDLL computes that difference directly.
QCDLL performance in multipath is not claimed optimum; I and others have shown other techniques for reducing multipath by estimating and subtracting multipath components to reduce bias error on the direct signal. The results shown here with the trapezoidal wave-shapes may approximate the best performance possible, since the trapezoid has no precursor/tail that would be removed by a multipath-estimating receiver.
The optimal discriminator channel reference waveforms (the differentiated pulse waveform) defined for the QCDLL for any filtered received signal can be approximated by a sequence of pulses. These sequences of pulses define a quasi-optimal set of weighted conventional early-late DLL or multi-correlator tracking receiver configuration that approximate the optimal reference, the differentiated signal.
More general symbol coding techniques include: NH, Barker, generalized Barker, chirp, and TM Rademacher and Walsh codes. Barker, Generalized Barker, and NH codes have greatly reduced autocorrelation sidelobes and excellent multipath performance. These can also be time and I/Q multiplexed. Variants of chirp and TM Rademacher, Walsh can provide both spectral shaping and improved multipath performance. Weighted TM Walsh-coded symbols can be designed to synthesize any discrete-time, time-limited realizable function. Ordinary legacy PN can be time-multiplexed with any of these BCS symbols, with perhaps another longer PN sequence to generate a composite signal where a tracking receiver can operate on both simultaneously and yet leave legacy receivers still operational. Although we have only shown equal weighting in the TM multiplexing, clearly the weighting can be varied by changing the duty factor.
Acknowledgments
I wish to acknowledge the suggestions of Chris Hegarty of MITRE, J.K. Holmes, Aerospace Corporation, and Per Enge and Grace Gao, Stanford University. I give special recognition to Hegarty, Betz, and Saidi for their generalized BCS work on NH and Barker codes, and the thesis of J. A. A. Rodriguez, University FAF Munich, also on generalized BCS. The detailed version of this article appears in the 2010 ION International Technical Meeting Proceedings, and contains about 50 references.
James Spilker is a consulting professor in electrical engineering, aeronautics, and astronautics at Stanford, and co-author of Global Positioning System: Theory and Applications, Volumes I, II.
Trimble has introduced an innovative Global Navigation Satellite System (GNSS) reference receiver for infrastructure, precise scientific, and network applications. The Trimble NetR9 GNSS reference receiver is a Continuously Operating Reference Station (CORS) receiver that can support the demanding applications for the earth science community and for the surveying, construction, mapping, and agricultural industries, Trimble said, adding that the NetR9 was designed to provide the user with maximum features and functionality from a single receiver.
The Trimble NetR9 reference receiver offers 440 channels for robust GNSS constellation tracking. The receiver supports a wide range of satellite signals, including GPS and GLONASS signals. In addition, Trimble is committed to providing Galileo-compatible products in advance of Galileo system availability, the company said. In support of this plan, the Trimble receiver is capable of tracking the experimental Galileo GIOVE-A and GIOVE-B test satellites for signal evaluation and test purposes.
The Trimble NetR9 reference receiver can be used as a standalone receiver or as part of a network solution. Specific applications include high-accuracy positioning as part of a Trimble VRS network, as a mobile field base station or CORS for real-time kinematic (RTK) corrections, as a scientific reference station collecting information for specialized studies, as a field campaign receiver for post-processing applications, and as support for Differential Global Positioning System (DGPS) coastal beacons. In addition, the Trimble NetR9 reference receiver can be used for monitoring the integrity of VRS networks as well as the deformation of physical infrastructure such as bridges, dams, mines, oil platforms, and other natural and manmade structures.
The Trimble NetR9 reference receiver’s large internal memory (8 GB) allows post-processed results for base stations to be computed after survey completion, improving the accuracy of the survey. The highly compressed secure internal memory allows for more than 20 years of 15-second dual-frequency GPS data storage. In addition, the NetR9 also has USB logging capability for additional storage capacity, Trimble said.
The receiver supports the new CMRx communications protocol, which provides correction compression for optimized bandwidth and full utilization of all satellites in view. This gives the customer more robust positioning data and reliable positioning performance, Trimble said.
Optimized for field use with built-in rechargeable batteries, the NetR9 reference receiver consumes very little power and can be used for projects with remote connectivity and in extreme weather conditions. It has an IP67 rating, which means it is sealed against dust and can survive immersion in up to a meter of water for approximately 30 minutes. It also meets MIL-STD 810F standard for drops, vibration, and temperature extremes.
The Trimble NetR9 has its physical memory built into the circuit board, providing greater protection of data, particularly under extreme conditions. Multiple built-in serial ports supply communications and power to support field use, whether connecting to a radio for RTK surveys, direct communication with a satellite phone for remote operations, or for ancillary input devices such as inclinometers and meteorological sensors, and it offers Bluetooth communication with a cell phone for real-time data streaming. In addition, both power and Ethernet can be supplied over a single cable using Power over Ethernet (PoE) technology.
Aeroflex has introduced the GPSG-1000, a portable GPS and Galileo positional simulator. The GPSG-1000 is lightweight and configurable. It fills a gap in the market by providing a low-cost 12-channel test set that creates three-dimensional simulations, Aeroflex said.
With the advent of GPS signal modernization, many GPS simulators on the market today are now obsolete, according to the company, which is based in Witchita, Kansas. The GPSG-1000 supports civil and military avionics field and bench maintenance technicians, production test technicians, and system integrators with a modern simulator for L1, C/A code and L1C, L2C, L5 GPS modernization signals, as well as new Galileo E1, E5, E6 services. It can be configured with single channel, 6-channel, or 12-channel simulation. Typical tests include acquisition sensitivity, tracking sensitivity, time-to-first-fix for cold/warm/hot starts, time-to-second-fix, positional accuracy, RAIM failure tolerance, and subsystem stimulation for 3D flight execution.
The Aeroflex GPSG-1000 uses modular technology for RF and baseband signal generation to produce highly accurate and repeatable test results. Unlike bench top simulators, Aeroflex’s approach also allows the test system to be upgraded at low cost.
Features include:
Simulation of GPS L1C, L2C, L5 signals, supporting the modernization of signals used by the latest designs of GPS receivers.
Simulation of Galileo E1, E5, E6 signals to support unencrypted services.
SBAS, WAAS/EGNOS L1, L5, for automatic SBAS simulation.
Built-in GPS C/A code receiver for automatic GPS almanac download.
Waypoint navigation, a 3D-navigation scheme that allows airport-to-airport flight plan simulation.
Programmable satellite parameters allow specific tests to be conducted to determine receiver behaviour under degraded or invalid signal conditions.
Dynamic satellite signal simulation for real-world constellation signal conditions.
The GPSG-1000 Portable Positional Simulator is available in single channel, 6-channel, and 12-channel configurations. The GPSG-1000 is available in 16 weeks upon receipt of order.
APP PLANET featured 100 exhibitors and a lounge for old-fashioned social networking.
By Moni Malek
It’s that time of year, around Valentine’s Day, when most of the who’s who in the mobile phone industry meet at the Mobile World Congress. I have been attending this event for nearly 15 years, and have seen the location change from Cannes to Barcelona, and the name change from GSM World Congress to 3GSM World Congress to Mobile World Congress.
At the same time, the number of mobile phone users shot up from the millions to the billions. A new feature this year was the App Planet hall. The attendance of 47,000 was only marginally down from the 49,000 visitors in 2009, making it still a very busy a event, with no sign of the recession compared to other shows I’ve seen. It’s still the best place to meet companies in the mobile space — I met 25 in three days, as well as running into ex-colleagues and contacts who, like me, have been attending for years.
Smartphone Entry. The trend of the last year or so has been the burst entry of smartphones. First started by Apple iPhone for consumers and to some extent Blackberry for professionals (the so-called fruit phones), operating systems (OS) have evolved to include Android from Google, Palm Pre’s webOS, Nokia and Intel merging their top-end smartphone operating systems, and Symbian going open source. Microsoft has people excited with Windows Phone 7, with the first handsets running on it scheduled to hit the markets around the holiday season.
Most of the smartphones are GPS-enabled, and as these phones increase the market penetration of GPS, GPS use will increase, leading to more use of location-based applications.
Deep Pockets. For those of you who think GPS personal navigation device market pricing is tough, the mobile phone market is cut throat. Volumes are out of this world, and in lots of countries around the globe, the volumes are more than the population! These volumes require deep pockets to keep up the investment to make money on decreasing margins.
There has been a trend toward consolidation in the GPS chip industry. Less than a year or two ago in Barcelona booths represented eRide (acquired by Furuno), Global Locate (acquired by Broadcom), GloNav (acquired by NXP, then wound up in ST Ericsson), Nemerix (which seems to have disappeared, though it’s rumored some assets went to another chip company), and finally SiRF (now part of CSR-SiRF). CSR-SiRF’s booth was more like a fortress, but at least I got to talk to the SiRF founder.
It will be interesting to see what a Bluetooth-GPS company with a lot of cash in the bank plans as a next move. As for survivors, u-blox still had a booth (they weren’t acquired; they did an Initial Public Offering), and CellGuide had a small section of the Israel booth.
App Planet. Since I first attended this show, global mobile-phone technology has gone from GSM voice to GPRS data to 3G voice/data to HSPA. Now comes LTE (Long Term Evolution), which is really a packet data network that can use VoIP. Together, 3G and smartphones give us an environment which lets apps become a new business model worth billions. The Apps Planet hall showcased a lot of these models. The hall didn’t exist last year, but this year had 100 exhibitors. It easy to predict this number will grow.
There are so many applications, they will need to differentiate to stand out from the crowd and gain mass. I think location-based apps need to get better, and I see that happening at the show. deCarta allows searches for places based on real walking distances or near the route you are traveling. Aloqa has clients for every smartphone with channels that you can choose for your interest. Mireo impressed me with not only natural text guidance (“turn left after the Apple store”) but its super-fast routing in less that 2 seconds, as opposed to 30-seconds-plus on other devices. It features algorithms with pre-stored routes to major junctions, so only the rest is routed. In any case, the net effect is you are routed before you have to think which way to drive or walk. I always say mobile phone users have short attention spans and expect instant gratification, and fast routing certainly helps.
Finally, an Audi A5 Cabriolet displayed a solution for the European Commission’s eCall emergency call initiative, a car which automatically sends your position after an accident to a Public Safety Answering Point. eCall should be implemented in Europe by 2014, but Qualcomm is looking to put the system into the Audi A8 this year.
Moni Malek is CEO of ML-C MobileLocation-Company GmbH, a new company integrating location and communication in a system platform.
Motorola’s Christian Kurzke discusses Android with developers.
By Ana P. C. Larocca, Ricardo E. Schaal, and Augusto C. B. Barbosa, University of São Paulo
Multipath makes it difficult to detect very low-frequency structural vibrations, ranging from 0.05 to 1 Hz, important in characterizing dynamic loads and determining safe structural lifetimes. The authors have developed a phase-residual method for use with very high-frequency data to distinguish receiver noise, multipath, and the periodic displacements that are most structurally significant. The methodology can apply to bridges, tall buildings, and towers.
Civil engineers continuously seek reliable methods and tools to improve the quality and lifetime of large structures. Most studies in this field have been based on static loading. Nowadays, dynamic loading has become a particular concern, and GPS offers direct measures of dynamic displacements of large structures induced by traffic, wind, and earthquakes.
Precisely characterizing the vibrations that are a common behavior of large structures such as bridges, tall buildings, and towers undergoing dynamic loads facilitates structural analysis studies. It is feasible to detect structural vibrations using a computational model and GPS sensors. The critical vibration frequencies of bridges detectable with different GPS positioning techniques (real-time kinematic, static, quasi-static) range from 0 to 0.3 Hz.
However, the unavoidable presence of multipath signals in the same frequency range makes it difficult to detect very low-frequency vibrations, mostly ranging from 0.05 up to 1 Hz, for short- to medium-span bridges.
Our preliminary results show that the structural vibration measurements, mixed with random amplitude and frequency signals generated by electronics and the ionosphere, together with slowly varying signals generated by multipath, can be better detected with an oversampled GPS data set. This hypothesis relies on fact that the structure oscillation is reasonably stable during the data-collecting period.
The analyses of GPS time series used were done by mathematical addition of well-known sine waves in the raw phase of a 100-Hz data set collected from a short baseline. This strategy simulates the antenna vibrating vertically on a structure, for example at the deck’s midpoint of a bridge.
Methodology
The methodology used to collect and analyze GPS data was developed for providing low-cost high-accuracy monitoring with single-frequency GPS receivers. The technique is the interferometry method based on the analysis of the L1 double-difference phase residuals of regular static observations. In this data-processing, one satellite is considered as a reference, and its selection is according to the direction of the vibration to be measured. The satellite not taken as a reference — located in the same direction as the vibration movement — has the residual values that contain information about bridge deckvibrations (phase changes). In 2001, we named this the phase-residual method (PRM); see “Millimeters in Motion” in GPS World, January 2005.
The residuals incorporate all phase deviations from the adjusted double-difference position during the observation. These phase deviations are due to electronic receiver noise, multipath, small dynamic antenna movements, and other error sources. Converting the residuals to the frequency domain by the fast Fourier transform (FFT) associated with a continuous wavelet transform (CWT), it is possible to see the different behaviors of the receiver phase noise,
multipath, and periodic vibration, enabling the distinction between them. The periodic displacement presents a peak due to the fundamental vibration mode, while the receiver noise presents a white-noise spectrum, and the multipath presents a broad spectrum close to zero frequency. The last feature is very dependent on how the antennas “see” their vicinity. As PRM does not need well-known coordinates epoch-by-epoch to determine the amplitude and the frequency values of the oscillations, it is possible to get reliability.
The spectrum analyses were done by FFT, which provides a design of the vibration’s peak amplitude values; the CWT was used to detect the variation of the frequency value during the timespan of observations, and for validating the results.
Simulation and Filtering
The preliminary investigation was done by the mathematical addition of sine waves on satellite signals close to zenith, which are the most affected by a vertical amplitude vibration in a real situation. The double-difference phase was calculated, taking as reference the lowest satellite.
The mathematically generated sine wave had peak-to-peak amplitude of 1 millimeter and frequency values ranging from 0.06 Hz up to 1 Hz. The analyses for sine-wave detection were done by applying the FFT and the CWT with the Morlet Wavelet, which deserves a short description.
The CWT was used because structural vibration signals with small peak-to-peak amplitudes in the low frequency region are not well represented in time and frequency by the FFT methods. A particular wavelet, Morlet, was used and is defined as
(1)
where wo is dimensionless frequency and η is dimensionless time. When using wavelets for feature extraction purposes, the Morlet wavelet is a good choice, because it provides a good balance between time and frequency localization.
The idea behind the CWT is to apply the wavelet as a band-pass filter to the time series. The CWT of a time series (f (t),t = 1,…,N) with uniform time steps dt, is defined as the convolution of f (t) with the complex combination of the mother wavelet scaled and normalized, as:
(2)
where Wj,k(t) represents the similarity between wavelet function and the analyzed time series f (t); that is, the higher the value of Wj,k(t), the greater the similarity between the analyzed function and the mother wavelet function that modulates the analyzed signal. The CWT was implemented in MATLAB software.
100-Hz Phase Data
Regarding the detection of low frequencies due to a small peak-to-peak amplitude vibration, it is important to show the L1 double-difference residuals of a 100-Hz data rate (Figure 1) and its spectrum before mathematically adding the sine-wave signal due to periodic vibrations. The figure shows the raw phase residuals of 20 seconds of data between two satellites, SV05 (lowest) and SV20 (highest).
FIGURE 1. Raw L1 double-difference phase residuals from a time series at a 100-Hz data rate.
Figure 2 presents a 1-second data span for better visualization of peak-to-peak amplitude of the raw double-difference phase residuals, which is lower than 3 millimeters.
FIGURE 2. Residuals from L1 double-difference phase residual.
Figure 3 was produced to verify the variability of 100-Hz residuals and the probability of errors in the signal that can contribute to degrading the identification of the sine-wave vibration peaks. The resulting histogram is close to a bell curve of a Gaussian distribution, demonstrating the good quality of the 100-Hz data. Figure 4 shows the Morlet CWT computed to identify the low-frequency bias term and a high-frequency noise term. The 5-percent significance (95-percent confidence) level of significant signal-wave information is delimited by a thick contour. The signal information of double-difference phase residuals was used as a reference for supporting a better distinction between noise and sine-wave signals.
FIGURE 3. The Gaussian distribution of 100-Hz data rate residuals.FIGURE 4. Continuous Wavelet Transform of the residual time series. The 5-percent significance level of sine wave detection is shown as a thick contour.
Zero-Baseline Test
A zero-baseline test was performed to determine the correct operation of a GPS receiver, associated antennas, and cabling. The objective was to verify the precision of the receiver. A 1-minute data sample was collected. Figure 5 shows the residuals of L1 double-difference phase.
FIGURE 5. Zero baseline 100-Hz data rate residuals of L1 double-difference phase.
Figure 6 shows 5 seconds of the zero-baseline data; the peak-to-peak amplitude of residuals is very small, close to 2.0 millimeters. This information leads us to expect detection of very low-frequency vibrations, ranging up to 0.3 Hz with a 1-millimeter amplitude displacement peak-to-peak.
FIGURE 6. Residuals from a zero baseline with 100-Hz data.
Figure 7 shows the spectrum of the zero-baseline residuals; it is possible to observe the region close to zero strongly affected by multipath. This makes the detection of very low frequencies difficult.
FIGURE 7. Power spectrum of a zero-baseline residual.
The CWT was applied to decomposing the zero-baseline double-differenced residuals into a low-frequency bias term and a low-frequency noise term. Figure 8 shows the behavior of the residuals of the 100-Hz phase data, where red regions represent the most suggestive energy level of the measurement noise term.
FIGURE 8. Morlet CWT of zero-baseline residual time series. The 5-percent significance level of sine-wave detection is shown as a thick contour.
Preliminary Simulation Results
Figure 9 illustrates the raw L1 double-difference phase residuals with a periodic sine wave of 1 millimeter peak-to-peak amplitude mathematically added to the time series. It is possible to observe the presence of the periodic signal.
FIGURE 9. Raw L1 residual time series with a sine wave of 1-Hz frequency and 1-millimeter amplitude.
Figure 10 shows that the stronger energy is close to 1 Hz due to the 1-Hz sine wave, as expected. The resulting well-defined peak is due to the high sampling rate provided by 100-Hz receivers. Figure 11 shows details of the peak due to the sine wave of 1 Hz added to the residuals.
FIGURE 10. Spectrum of L1 double-difference phase residuals with a sine wave of 1 Hz and 1 millimeter.FIGURE 11. Close-up of region with the most power at 1 Hz.
We analyzed these data with the Morlet CWT to find events to compared when other low frequencies had been simulated, helping separate noise from signal. Figure 12 presents the standardized time-series residuals, showing a region with highest power level. The continuous red region corresponds to a 1-Hz sine wave, and the spread-out red-orange regions may be due to electronic noise and multipath. The region outside the cone, delimited by the thick contour, indicates the detection of significant signal information but without the 95-percent confidence.
FIGURE 12. Morlet CWT of time series of residuals with 1-Hz sine wave with 1 millimeter amplitude. The 5-percent significance level of sine-wave detection is shown as a thick contour.
0.5-Hz Sine Wave. The second sine wave generated had the same peak-to-peak amplitude, 1 millimeter, and the frequency value of 0.5 Hz. Figure 13 illustrates the raw L1 double-difference phase residuals with a periodic 0.5-Hz sine wave mathematically added to the time series.
FIGURE 13. Raw L1 double-difference phase residuals with a sine wave of 0.5 Hz.
Figure 14 shows an energy peak at a frequency of approximately 0.5 Hz, also with a well defined peak.
FIGURE 14. Spectrum of L1 double-difference phase residuals with a sine wave of 0.5 Hz.
Figure 15 shows details of the peak.
FIGURE 15. Close-up of region with the most power at 0.5 Hz.
The CWT in Figure 16 shows that the intensity energy level represented by the red continuous region and the spread-out red-orange regions are quite similar to those of the CWT of the 1-Hz sine wave (Figure 12). Note a decrease in energy intensity (orange-yellow) that occurs due to decreased signal sampling of the 0.5-Hz signal (10 cycles) in 20 seconds of data, compared to 1 Hz (12 cycles) in the same 20 seconds.
FIGURE 16. Morlet CWT of time series of residuals with 0.5 Hz sine wave with 1 mm amplitude. The 5-percent significance level of sine wave detection is shown as a thick contour.
0.1-Hz Sine Wave. The third sine wave mathematically generated had the same peak-to-peak amplitude, 1 millimeter, and a frequency of 0.1 Hz. Figure 17 illustrates the raw L1 double-difference phase residuals with the periodic 0.1-Hz sine wave mathematically added to the time series. Figure 18 shows the power at one frequency, approximately 0.10 Hz, still with a well-defined peak.
FIGURE 17. Raw L1 double-difference phase residuals with a sine wave of 0.10 Hz.FIGURE 18. Close-up of region with the most power at 0.10 Hz.
Figure 19 presents identification of the 0.1-Hz sine wave by CWT with the 5-percent significance level shown as a thick contour. A decrease of energy intensity (orange-yellow) occurs due to decreased signal sampling of 0.1 Hz (2.5 cycles) in 20 seconds of data compared to 0.5 Hz (10 cycles) in the same 20 seconds.
FIGURE 19. Morlet CWT of time series of residuals with 0.1-Hz sine wave with 1-millimeter amplitude; 5-percent significance level of sine wave detection shown as a thick contour.
0.08-Hz Sine Wave. We simulated a sine wave of this frequency (Figure 20). Figure 21 presents identification of the 0.08-Hz sine wave by CWT through the 5-percent significance level shown as a thick contour. A decrease in energy intensity (orange-yellow) occurs due to decreased signal sampling of 0.08 Hz (almost two cycles) in 20 seconds of data compared to 0.5 Hz (ten cycles) in the same 20 seconds.
FIGURE 20. Close-up of region with most power at 0.08 Hz.FIGURE 21. Morlet CWT of time series of residuals with 0.08 Hz sine wave with 1-millimeter amplitude; 5-percent level of sine-wave detection shown as a thick contour.
0.06-Hz Sine Wave. Finally, a 0.06-Hz sine wave was simulated and added to the residuals, but the FFT spectral analysis did not present the power peak. This can be attributed due to the sine-wave period providing only 1.5 cycles during 20 seconds and did not generate enough power to be detected by FFT.
Figure 22 presents a close-up view of 0.06-Hz sine-wave power spectrum of the residuals not indicating a significant peak close to the expected frequency region.
FIGURE 22. Power spectrum of double-difference phase residuals with 0.06-Hz sine-wave signal.
The investigation continued with a Morlet CWT. In Figure 23 it is possible to verify the presence of a faded red region close to the period corresponding to 0.06 Hz — at the bottom of figure and under the cone’s thick contour — signalling that the wavelet was able to detect a very low frequency even with a small sampling. However, due to small signal sampling, the detection is not within a 95-percent confidence. Otherwise, if the time series had lasted more than 20 seconds, certainly the sine wave would have been detected.
FIGURE 23. Morlet CWT of time series of residuals with 0.06 Hz sine wave with 1-millimeter amplitude.
These analyses suggest that longer time-series data would enable detection of very low frequencies with 95-percent confidence.
Conclusions
The lack of amplitude accuracy does not constitute a significant restriction in large structure monitoring, as the exactness of its natural oscillating frequency, harmonics, and response to external dynamic forces are more important for identification of a structural problem.
Using 100-Hz receivers to detect very low-frequency vibrations, the combination of 100-Hz data with filtering techiniques enables detection of signal vibrations of very low frequencies. The tests were conducted using a mathematical simulation of sine waves added to raw residuals of L1 double-difference phase.
The results of simulations and filtering techniques indicate that very low frequency vibrations can be detected when the sampling rate of GPS data and the sampling frequency of an embedded sine wave is large.
Additionally, zero baseline and static short baseline trials have been conducted to assess the noise of the receivers that is close to 2.5 millimeters — extremely low and contributing to detection of vibrations with low peak-to-peak amplitude.
Spectral analysis is a fundamental tool for engineering development. Despite such new analysis concepts as FFT and CWT used here, as well as higher-order spectra, basic frequency domain analysis will remain the practical analysis tool in the foreseeable future.
Future tests will be carried out collecting 100-Hz data, sufficient for having oversampling of sine-wave frequencies due to structural vibrations, and using a new methodology with just one GPS receiver.
Acknowledgments
Thanks to the JAVAD GNSS Moscow Research and Development team for providing a Triumph receiver and 100-Hz data through Michael Glutting, whom we also thank. The researchers received a sponsorship from the National Counsel of Technological and Scientific Development Government (CNPq) of the Brazil Federal Government to purchase a pair of 100-Hz data-rate GPS receivers.
Manufacturers
The 20 seconds of data were kindly provided by JAVAD GNSS Moscow Research and Development team and were collected using Javad GNSS Triumph receivers with JNS choke-ring antennas.
Ana P.C. LaRocca is a lecturer in the Department of Transportation Engineering of the Polytechnic School at the University of São Paulo (USP) and holds a Ph.D from that same institution.
Ricardo E. Schaal is an associate professor with a Ph.D. from USP.
Augusto C. B. Barbosa is a Ph.D candidate at the Institute of Astronomy, Geophysics and Atmospheric Sciences, at USP.
By Axel van den Berg, Tom Willems, Graham Pye, and Wim de Wilde, Septentrio Satellite Navigation, Richard Morgan-Owen, Juan de Mateo, Simone Scarafia, and Martin Hollreiser, European Space Agency
A fully stand-alone, multi-frequency, multi-constellation receiver unit, the TUR-N can autonomously generate measurements, determine its position, and compute the Galileo safety-of-life integrity.
Development of a reference Galileo Test User Receiver (TUR) for the verification of the Galileo in-orbit validation (IOV) constellation, and as a demonstrator for multi-constellation applications, has culminated in the availability of the first units for experimentation and testing. The TUR-N covers a wide range of receiver configurations to demonstrate the future Galileo-only and GPS/Galileo combined services:
Galileo single- and dual-frequency Open Services (OS)
Galileo single- and dual-frequency safety-of-life services (SoL), including the full Galileo navigation warning algorithms
Galileo Commercial Service (CS), including tracking and decoding of the encrypted E6BC signal
GPS/SBAS/Galileo single- and dual- frequency multi-constellation positioning
Galileo single- and dual-frequency differential positioning.
Galileo triple-frequency RTK.
In parallel, a similar test user receiver is specifically developed to cover the Public Regulated service (TUR-P). Without the PRS components and firmware installed, the TUR-N is completely unclassified.
Main Receiver Unit
The TUR-N receiver is a fully stand-alone, multi-frequency, multi-constellation receiver unit. It can autonomously generate measurements, determine its position, and compute Galileo safety-of-life integrity, which is output in real time and/or stored internally in a compact proprietary binary data format.
The receiver configuration is fully flexible via a command line interface or using the dedicated graphical user interface (GUI) for monitoring and control. With the MCA GUI it is also possible to monitor the receiver operation (see Figure 1), to present various real-time visualizations of tracking, PVT and integrity performances, and off-line analysis and reprocessing functionalities. Figure 2 gives an example of the correlation peak plot for an E5 AltBOC signal.
FIGURE 1. TUR-N control screen.FIGURE 2. E5 AltBOC correlation peak.
A predefined set of configurations that map onto the different configurations as prescribed by the Test User Segment Requirements (TUSREQ) document is provided by the receiver.
The unit can be included within a local network to provide remote access for control, monitoring, and/or logging, and supports up to eight parallel TCP/IP connections; or, a direct connection can be made via one of the serial ports.
Receiver Architecture
The main receiver unit consists of three separate boards housed in a standard compact PCI 19-inch rack. See Figure 3 for a high-level architectural overview.
FIGURE 3. Receiver architecture.
A dedicated analog front-end board has been developed to meet the stringent interference requirements. This board contains five RF chains for the L1, E6, E5a/L5, E5b, and E5 signals. Via a switch the E5 signal is either passed through separate filter paths for E5a and E5b or via one wide-band filter for the full E5 signal. The front-end board supports two internal frequency references (OCXO or TCXO) for digital signal processing (DSP).
The DSP board hosts three tracker boards derived from a commercial dual-frequency product family. These boards contain two tracking cores, each with a dedicated fast-acquisition unit (FAU), 13 generic dual-code channels, and a 13-channel hardware Viterbi decoder. One tracking core interacts with an AES unit to decrypt the E6 Commercial Service carrier; it has a throughput of 149 Mbps.
Each FAU combines a matched filter with a fast Fourier transform (FFT) and can verify up to 8 million code-frequency hypotheses per second. Each of the six tracker cores can be connected with one of the three or four incoming IF streams. To simplify operational use of the receiver, two channel-mapping files have been defined to configure the receiver either for a 5-frequency 13-channel Galileo receiver, or for a dual-frequency 26-channel Galileo/GPS/SBAS receiver. Figure 4 shows all five Galileo signal types being tracked for nine visible satellites at the same time.
FIGURE 4. C/N0 plot with nine satellites and all five Galileo signal types: L1BC (green), E6BC (blue), E5a (red), E5b (yellow), and E5 Altboc (purple).
The receiver is controlled using a COTS CPU board that also hosts the main positioning and integrity algorithms. The processing power and available memory of this CPU board is significantly higher than what is normally available in commercial receivers. Consequently there is no problem in supporting the large Nequick model used for single-frequency ionosphere correction, and achieving the 10-Hz update rate and low latency requirements when running the computationally intensive Galileo integrity algorithms. For commercial receivers that are normally optimized for size and power consumption, these might prove more challenging.
The TUR project included development of three types of Galileo antennas:
a triple-band (L1, E6, E5) high-end antenna for fixed base station applications including a choke ring;
a triple-band (L1, E6, E5) reference antenna for rover applications;
a dual-band (L1, E5b) aeronautic antenna for SOL applications
Figure 5 shows an overview of the main interfaces and functional blocks of the receiver, together with its antenna and a host computer to run the MCA software either remotely or locally connected.
FIGURE 5. TUR-N with antenna and host computer.
Receiver Verification
Currently, the TUR-N is undergoing an extensive testing program. In order to fully qualify the receiver to act as a reference for the validation of the Galileo system, some challenges have to be overcome. The first challenge that is encountered is that the performance verification baseline is mainly defined in terms of global system performance. The translation of these global requirements derived from the Galileo system requirements (such as global availability, accuracy, integrity and continuity, time-to-first/precise-fix) into testable parameters for a receiver (for example, signal acquisition time, C/N0 versus elevation, and so on) is not trivial. System performances must be fulfilled in the worst user location (WUL), defined in terms of dynamics, interference, and multipath environment geometry, and SV-user geometry over the Galileo global service area.
A second challenge is the fact that in the absence of an operational Galileo constellation, all validation tests need to be done in a completely simulated environment. First, it is difficult to assess exactly the level of reality that is necessary for the various models of the navigation data quality, the satellite behaviour, the atmospheric propagation effects, and the local environmental effects. But the main challenge is that not only the receiver that is being verified, also the simulator and its configuration are an integral part of the verification. It is thus an early experience of two independent implementations of the Galileo signal-in-space ICD being tested together. At the beginning of the campaign, there was no previously demonstrated or accepted test reference.
Only the combined efforts of the various receiver developments benchmarked against the same simulators together with pre-launch compatibility tests with the actual satellite payload and finally IOV and FOC field test campaigns will ultimately validate the complete system, including the Galileo ground and space segments together with a limited set of predefined user segment configurations. (Previously some confidence was gained with GIOVE-A/B experimental satellites and a breadboard adapted version of TUR-N). The TUR-N was the first IOV-compatible receiver to be tested successfully for RF compatibility with the Galileo engineering model satellite payload.
Key Performances
Receiver requirements, including performance, are defined in the TUSREQ document.
Antenna and Interference. A key TUSREQ requirement focuses on receiver robustness against interference. It has proven quite a challenge to meet the prescribed interference mask for all user configurations and antenna types while keeping many other design parameters such as gain, noise figure, and physical size in balance. For properly testing against the out-of-band interference requirements, it also proved necessary to carefully filter out increased noise levels created by the interference signal generator.
Table 2 gives an overview of the measured values for the most relevant Antenna Front End (AFE) parameters for the three antenna types. Note: Asymmetry in the AFE is defined as the variation of the gain around the centre frequency in the passband. This specification is necessary to preserve the correlation peak shape, mainly of the PRS signals.
The gain for all antenna front ends and frequencies is around 32 dB. Figures 6 and 7 give an example of the measured E5 RHCP radiating element gain and axial ratio against theta (the angle of incidence with respect to zenith) for the high-end antenna-radiating element. Thus, elevation from horizontal is 90-theta.
UERE Performance. As part of the test campaign, TUR performance has been measured for user equivalent range error (UERE) components due to thermal noise and multipath.
TUSREQ specifies the error budget as a function of elevation, defined in tables at the following elevations: 5, 10, 15, 20, 30, 40, 50, 60, 90 degrees. The elevation dependence of tracking noise is immediately linked to the antenna gain pattern; the antenna-radiating element gain profiles were measured on the actual hardware and loaded to the Radio Frequency Constellation Simulator (RFCS), one file per frequency and per antenna scenario. The RFCS signal was passed through the real antenna RF front end to the TUR. As a result, through the configuration of RFCS, real environmental conditions (in terms of C/N0) were emulated in factory.
The thermal noise component of the UERE budget was measured without multipath being applied, and interference was allowed for by reducing the C/N0 by 3 dB from nominal. Separately, the multipath noise contribution was determined based on TUSREQ environments, using RFCS to simulate the multipath (the multipath model configuration was adapted to RFCS simulator multipath modeling capabilities in compliance with TUSREQ). To account for the fact that multipath is mostly experienced on the lower elevation satellites, results are provided with scaling factors applied for elevation (“weighted”), and without scaling factors (“unweighted”). In addition, following TUSREQ requirements, a carrier smoothing filter was applied with 10 seconds convergence time.
Figure 8 shows the C/N0 profile from the reference antenna with nominal power reduced by 3 dB. Figure 9 shows single-carrier thermal noise performance without multipath, whereas Figure 10 shows thermal noise with multipath. Each of these figures includes performance for five different carriers: L1BC, E6BC, E5a, E5b, and E5 AltBOC, and the whole set is repeated for dual-frequency combinations (Figure 11 and Figure 12).
FIGURE 8. Reference antenna, power nominal-3 dB, C/N0 profile.FIGURE 9. Reference antenna, power nominal-3 dB, thermal noise only, single frequency.FIGURE 10. Reference antenna, power nominal-3 dB, thermal noise with multipath, single frequency.FIGURE 11. Reference antenna, power nominal-3 dB, thermal noise only, dual frequency.FIGURE 12. Reference antenna, power nominal-3 dB, thermal noise with multipath, dual frequency.
The plots show that the thermal noise component requirements are easily met, whereas there is some limited non-compliance on noise+multipath (with weighted multipath) at low elevations. The tracking noise UERE requirements on E6BC are lower than for E5a, due to assumption of larger bandwidth at E6BC (40MHz versus 20MHz). Figures 9 and 10 refer to UERE tables 2 and 9 of TUSREQ. The relevant UERE requirement for this article is TUSREQ table 2 (satellite-only configuration). TUSREQ table 9 is for a differential configuration that is not relevant here.
UERRE Performance. The complete single-frequency range-rate error budget as specified in TUSREQ was measured with the RFCS, using a model of the reference antenna. The result in Figure 13 shows compliance.
FIGURE 13. UERRE measurements.FIGURE 14. L1 GPS CA versus E5 AltBOC position accuracy (early test result).
Position Accuracy. One of the objectives of the TUR-N is to demonstrate position accuracy. In Figure 14 an example horizontal scatter plot of a few minutes of data shows a clear distinction between the performances of two different single-frequency PVT solutions: GPS L1CA in purple and E5AltBOC in blue. The red marker is the true position, and the grid lines are separated at 0.5 meters. The picture clearly shows how the new E5AltBOC signal produces a much smoother position solution than the well-known GPS L1CA code. However, these early results are from constellation simulator tests without the full TUSREQ worst-case conditions applied.
FIGURE 14. L1 GPS CA versus E5 AltBOC position accuracy (early test result).
The defined TUSREQ user environments, the basis for all relevant simulations and tests, are detailed in Table 3. In particular, the rural pedestrian multipath environment appears to be very stringent and a performance driver.
This was already identified at an early stage during simulations of the total expected UERE and position accuracy performance compliance with regard to TUSREQ, summarized in Table 4, and is now confirmed with the initial verification tests in Figure 10. UERE (simulated) total includes all other expected errors (ionosphere, troposphere, ODTS/BGD error, and so on) in addition to the thermal noise and multipath, whereas the previous UERE plots were only for selected UERE components. The PVT performance in the table is based on service volume (SV) simulations.
The non-compliances on position accuracy that were predicted by simulations are mainly in the rural pedestrian environment. According to the early simulations:
E5a and E5b were expected to have 43-meter vertical accuracy (instead of 35-meter required).
L1/E5a and L1/E5b dual-frequency configurations were expected to have 5-meter horizontal, 12-meter vertical accuracy (4 and 8 required).
These predictions appear pessimistic related to the first position accuracy results shown in Table 5. On single frequency, the error is dominated by ionospheric delay uncertainty. These results are based on measurements using the RFCS and modeling the user environment; however, the simulation of a real receiver cannot be directly compared to service-volume simulation results, as a good balance between realism and worst-case conditions needs to be found. Further optimization is needed on the RFCS scenarios and on position accuracy pass/fail criteria to account for DOP variations and the inability to simulate worst environmental conditions continuously.
Further confirmations on Galileo UERE and position accuracy performances are expected after the site verifications (with RFCS) are completed, and following IOV and FOC field-test campaigns.
Acquisition. Figure 15 gives an example of different signal-acquisition times that can be achieved with the TUR-N after the receiver boot process has been completed. Normally, E5 frequencies lock within 3 seconds, and four satellites are locked within 10 seconds for all frequencies. This is based on an unaided (or free) search using a FAU in single-frequency configurations, in initial development test without full TUSREQ constraints.
FIGURE 15. Unaided acquisition performance.
When a signal is only temporarily lost due to masking, and the acquisition process is still aided (as opposed to free search), the re-acquisition time is about 1 second, depending on the signal strength and dynamics of the receiver. When the PVT solution is lost, the aiding process will time out and return to free search to be robust also for sudden user dynamics.
More complete and detailed time-to-first-fix (TTFF) and time-to-precise-fix (TTPF), following TUSREQ definitions, have also been measured.
In cold start the receiver has no prior knowledge of its position or the navigation data, whereas in warm start it already has a valid ephemeris in memory (more details on start conditions are available in TUSREQ). Table 6 shows that the acquisition performances measured are all compliant to TUSREQ except for warm start in E5a single frequency and in the integrity configurations. However, when the navigation/integrity message recovery time is taken off the measurement (as now agreed for updated TUSREQ due to message limitations), these performances also become compliant.
Specific examples of statistics gathered are shown in figures 16–21, these examples being for dual-frequency (E5b+L1) with integrity configuration. The outliers, being infrequent results with high acquisition times, are still compliant with the maximum TTFF/TTPF requirements, but are anyway under further investigation.
FIGURE 16. TTFF cold-start performance, dual frequency with integrity E5b+L1.FIGURE 17. TTFF cold-start distribution, dual frequency with integrity E5b+L1.FIGURE 18. TTPF cold-start performance, dual frequency with integrity E5b+L1.FIGURE 19. TTPF cold-start distribution, dual frequency with integrity E5b+L1.FIGURE 20. TTFF warm-start performance, dual frequency with integrity E5b+L1.FIGURE 21. TTFF warm-start distribution, dual frequency with integrity E5b+L1,
Integrity Algorithms. The Galileo SoL service is based on a fairly complex processing algorithm that determines not only the probability of hazardous misleading information (PHMI) based on the current set of satellites used in the PVT computation (HPCA), but also takes into consideration the PHMI that is achieved when one of the satellites used in the current epoch of the PVT computation is unexpectedly lost within the following 15 seconds. PHMI is computed according to alarm limits that are configurable for different application/service levels. These integrity algorithms have been closely integrated into the PVT processing routines, due to commonality between most processing steps.
Current test results of the navigation warning algorithm (NWA) indicate that less than 10 milliseconds of processing time is required for a full cycle of the integrity algorithms (HPCA+CSPA) on the TUR-N internal CPU board. Latency of the availability of the integrity alert information in the output of the receiver after it was transmitted by the satellite has been determined to be below 400 milliseconds. At a worst-case data output rate of 10 Hz this can only be measured in multiples of 100 millisecond periods. The total includes 100 milliseconds of travel time of the signal in space and an estimated 250 milliseconds of internal latency for data-handling steps as demodulation, authentication, and internal communication to make the data available to the integrity processing.
Conclusions
The TUR-N is a fully flexible receiver that can verify many aspects of the Galileo system, or as a demonstrator for Galileo/GPS/SBAS combined operation. It has a similar user interface to commercial receivers and the flexibility to accommodate Galileo system requirements evolutions as foreseen in the FOC phase without major design changes.
The receiver performance is in general compliant with the requirements. For the important safety-of-life configuration, major performance requirements are satisfied in terms of acquisition time and position accuracy.
The receiver prototype is currently operational and undergoing its final verification and qualification, following early confirmations of compatibility with the RFCS and with the Galileo satellite payload.
A packed audience attended the National Physical Laboratory in the United Kingdom for a February 23 meeting titled, “GPS Jamming and Interference: A Clear and Present Danger,” organized by the Digital Systems Knowledge Transfer Network.
In his keynote address, David Last described a dark, silent and dangerous world without GPS. He regaled attendees with tales from his experience as a GPS forensic expert, assisting the police who beat a path to his door bearing interesting boxes that turned out to be all sorts of jammers: of GNSS, of mobile phones, and of other radio systems. Last pointed to the near future when he believes that spoofers will undoubtedly make an appearance. The defences are limited: detection, prosecution, and the use of alternative sources of positioning, navigation, and timing information, perhaps eLoran.
His final insight was this: “Navigation is no longer about how to measure where you are accurately. That’s easy. Now it’s how to do so reliably, safely, robustly.”
Jim Doherty, from the U.S. Institute of Defense Analyses, discussed the use of existing resources for time and frequency backup. Drawing on his experience, Doherty delivered three overarching thoughts:
use all available means;
re-use existing systems where possible; and
produce integrated time and navigation.
He advised the audience to be conservative with their designs and not to go too close to the boundary conditions. He also noted that there is an important trade-off between independence and cost when considering complementary systems. Finally, he identified a potential need for eLoran to support synchronisation in aviation’s multi-lateration systems.
Moving on, Alan Grant of the UK General Lighthouse Authorities (GLA) described recent GPS jamming trials. He demonstrated that GPS jamming has wildly different effects, ranging from total denial to hazardously misleading information (HMI). HMI was particularly problematic: it caused the ship’s GPS receivers to report a realistic course and speed well away from the truth that was provided by the GLA’s eLoran system. He noted that the impact depends on the ship’s bridge design.
Professor and consultant Martyn Thomas spoke on an ongoing Royal Academy of Engineering study on GPS vulnerability, which brings together experts from across the UK and will report in early June.
This was followed by three presentations on coverage prediction by Robert Watson of Bath University, on interference detection using the U.S. National Geospatial Intelligence Agency’s GPS Jammer Location (JLOC) system by Alison Brown of NavSys Corporation, and on the GNSS Availability, Accuracy, Reliability anD Integrity Assessment for Timing and Navigation (GAARDIAN) interference detection system by Charles Curry of Chronos Technology.
The conference audience learned that any system can be jammed, that JLOC detects thousands of jammers on a daily basis — nearly all of them unintentional — and that the GAARDIAN system has integrated GPS, eLoran, and clocks for interference detection and mitigation.
Tom Willems from Septentrio and Peter McIlroy from Raytheon gave a good overview of what can be done with receivers and antennas. Willems focused on pulse blanking and adaptive notch filtering. He saw a clear trend towards hybridization, and confirmed that manufacturers recognise that GNSS is not a golden bullet — they can mitigate some interference but not all.
Peter McIlroy told listeners to “defeat interference and jamming before you detect it.” This included hybridization with inertial systems, putting some form of barrier between the antenna and the jammer, and the use of controlled pattern-reception antennas. He suggested that controlled pattern-reception antennas might become available for civil use.
Finally, Paul Groves from the University College London gave a very useful overview on positioning without GNSS. He addressed radio and non-radio systems and presented a fascinating chart that related the various radio systems in terms of range and lifecycle (Figure 1). The message was very timely given the need for complementary systems expressed by all speakers.
FIGURE 1. Range and lifecycles of current radio systems (courtesy Paul Groves).
I then chaired a lively panel discussion with David Last, Martyn Thomas, Charles Curry, Jim Doherty, and Tom Willems. I led off by focusing the discussion on resilient PNT, referring to the UK Center for the Protection of National Infrastructure’s definition for resilience: the equipment and architecture used are inherently reliable, secured against obvious external threats, and capable of withstanding some degree of damage.
The panel agreed on the need for hybrid solutions with multiple technologies. It expressed concerns that cheap GPS receivers are components in many systems, and it is too easy to overlook them. Martyn Thomas brought insight from the computing world and noted that we need to avoid single points of failure and to demonstrate independence.
Do our governments understand and should they do more? The panel thought that different governments are at different points on a journey, and that very few policymakers understand how a loss of GPS impacts critical national infrastructure. It was suggested that the European Union lags behind, due to the focus on Galileo.
This led to an interesting discussion about economics and funding. Martyn Thomas said that GPS vulnerabilities have grown, and that GPS competitors have disappeared for economic reasons, leaving us dependent on GPS. He pointed out that there are limited mechanisms for sharing funding and questioned whether there are many (any) organisations that are prepared to take the risk.
If you have limited funding, should it be used for detection or mitigation? The panel agreed that both were needed, but the prevailing view was that mitigation is more important, and that this needs to be supported by human factors activity.
In Summary. GNSS interference is a real and present danger. It is probably more widespread than generally assumed, and it is here to stay. We can harden our GNSS systems with improved receiver and antenna design, but this will mitigate only some interference, not all. The problem is cost. Cheap — and vulnerable — GNSS receivers will inevitably find their way, unseen, to the heart of our critical infrastructure. We need resilient positioning, navigation, and timing based on independent and complementary systems and sensors. Demonstrating independence is vital but not necessarily straightforward, and true independence costs money. The greatest challenge is helping policymakers understand the risks of relying on vulnerable systems and the need for resilience.
Finally, I return to Jim Doherty’s overarching thoughts: use all available means; re-use existing systems where possible; and produce integrated time and navigation.
eLoran, anyone?
SALLY BASKER is director of research and radionavigation for the General Lighthouse Authorities of the United Kingdom and Ireland.
Anthony Russo, director of the U.S. National Space-Based PNT Coordination Office, told the Munich Satellite Navigation Summit last month that, regarding the May 7, 2009, U.S. General Accountability Office report that forecast gaps in constellation availability, “The GAO will revise its report somewhat. They were using a model that was a little too cautious, one used by the [GPS] Wing. But satellites on orbit have been performing past estimated life. Further, we can turn off secondary payloads to conserve energy onboard satellites [and thus extend life] if needed.”
GPS satellites have proven themselves very hardy in space, outlasting their predicted lifetimes. Relying on those longer lives, the Air Force has saved money by replenishing upon need. But the GAO report apparently used more conservative lifetimes for the mathematical models of constellation availability. When those models were projected against the real-world timelines for IIF and Block III, some gaps appeared. Now the GAO and the Wing will re-undertake this exercise, factoring instead the longer lifetimes that the satellites have proved capable of.
In a hearing before the U.S. Senate Subcommittee on Strategic Forces, Committee on Armed Services on March 10, the following exchange occurred.
Senator BEN NELSON. “Ms. Chaplain, last year, the GAO issued a report that resulted in some significant and very negative press coverage about the health and reliability of the GPS system. Could you update us on the GAO’s assessment, now, of the GPS system?”
Ms. CHAPLAIN (Director, Acquisition and Sourcing Management,
from the Government Accountability Office (GAO)).
“Yes. We’re currently conducting a review—a follow- on review. And the two programs we looked at, on the satellite side last year, were the IIF program and the IIIA program. And the IIF program has made some progress, and it’s getting ready for a launch fairly soon.
“The IIIA program is on—it’s meeting its schedule currently. We still have concerns about the compressed nature of the schedule, and all the very difficult activities ahead for GPS IIIA, but it is not encountering any severe problems at this point.
“When we look at the health of the Constellation, our findings are pretty similar to last year’s. One thing we weren’t discussing in last year’s report, that should probably brought out more when we talk about it this year, is some of the options the Air Force has available to it to manage GPS if they do have—experience some dips in the Constellation availability. There are options that they have to get through those periods.
“Our concern is, you just—you don’t want to find yourself in a state where you’re looking at those kind of options; you want to make sure you do everything you can to keep the program healthy, resourced, and on track.”
A recent story in Spaceflight Now attributes to Gary Payton, the undersecretary of the Air Force for space, a statement that the Air Force currently has under review an option is to move some high-inclination flights, including future GPS satellite launches from Cape Canaveral to Vandenberg Air Force Base in California.
“We would like to be able to get to the point where we can project six months or a year down the road that we’re going to have a surge of launches all ganged too close together, that we may pull a GPS launch over to Vandenberg,” the story quotes Payton as saying. “The same rocket and orbitology allows you to launch out of Vandenberg.”
By Steven M. Di Naso, Vincent P. Gutowski, Harvey Henson, and Ryan Leonard
During the winter of 1838–39, the great Native American Cherokee Nation trekked across southern Illinois, in a forced removal by the U.S. government from their ancestral homeland in Tennessee. Harried, unequipped, and unsupported by their captors, thousands died on the Trail of Tears. Burial records were not kept, and burial locations remain lost to this day. Local history suggests that some Illinois settlers allowed the Cherokee to bury their dead on small plots of land adjacent to their own family cemeteries. One such plot, the Campground Presbyterian Church cemetery near Anna, Illinois, may contain unmarked Cherokee graves.
Researchers from Southern Illinois University and Eastern Illinois University used GPS to navigate and precisely map probes of a ground-penetrating radar (GPR) instrument in the cemetery. We monumented the geophysical survey grids using real-time kinematic (RTK) DGPS. Site topography was also mapped using GPS, as were the individual cemetery headstones. Adding geographic information systems (GIS) software to our mix to map cemetery headstone distribution and record headstone attributes (dates of death, names), we could determine chronological gaps within the cemetery that coincide with the probable emigration of the Cherokee.
GPR and electromagnetic conductivity produced contour plots of high-resolution magnetic gradient data. Small dipolar anomalies detected are typically related to disruptions within near-surface soil horizons and may correspond to locations of shallow graves: the lost final resting places of many Cherokee.
By close examination of the geophysical survey data and the anomalies produced from them, we were able to present plausible if not possible locations of several gravesites. However, at this time, and for obvious reasons, the actual location must remain secure and cannot be published.
The figure below shows a mosaic of amplitude depth slices at .30–.70 meter intervals from processed interpolated 250-MHz GPR profile data. White rectangles denote known graves. Most marked graves were imaged, although some were represented as more subtle anomalies on this display. Some possible unmarked graves were interpreted at UTM coordinates xxxx, yyyy.
The cemetery is within working distance of CORS station ILCB at Southern Illinois University. Two RTK GPS units communicating with the station via CDMA cellular radio used real-time differential corrections along a variable baseline length of approximately 28.5 kilometers, enabling mapping of the site at centimeter-accuracy resolution.
Survey data were edited, mapped, and analyzed with a GIS. Family genealogy polygons were generated using last names, to produce family distribution plots throughout the cemetery.
Manufacturers
The study, supported by a National Park Service grant with Southern Illinois University at Carbondale, used two Leica 1250 RTK GPS units, a Leica TC802 robotic total station, and Esri ArcGIS ArcInfo. Equipment was provided by Kara Company of Countryside, Illinois.
I read Don Jewell’s column in the March Defense PNT newsletter (see env-gpsworld-integration.kinsta.cloud/othershoe), on the troubling concern about GPS dependency, with considerable interest. I thought he made some excellent points, and, in my capacity as a member of GPS World’s Editorial Advisory Board, I would like to present some further thoughts for consideration.
I thought Don was pretty fair with General Schwartz’ comments, including the thinly veiled reference to underlying Air Force (AF) motives toward a smaller GPS constellation. However, in addition to focusing on the comments of one senior individual, you might also give some thought to the actions and motives of many in both the civil and military communities who have not only failed to embrace but have also resisted the advancement of a National Positioning, Navigation and Timing (PNT) Architecture and the holistic management framework necessary to implement it.
After 2-plus years of work by 30-plus government agencies (military and civil), an enterprise-level view of the PNT Architecture was presented to the public at the ION conference in Savannah in 2008. Since that time, discussions regarding its implementation have proceeded very slowly within the government. The Architecture contains all the elements you identify as contributing to the “Perfect Handheld GPS,” though, at the enterprise level, many have not technologically matured to the necessary system-of-systems level that would permit acquisition decisions under government rules. As you know, that will take focused technical analysis and trade studies, as well as further development in some cases to bring promising technologies along. Commercial industry does it faster, but its solutions are in most cases unique and proprietary, and not necessarily applicable for use by government agencies, particularly the military.
You also advocate for more tightly integrated GPS capability, “resulting in impregnable GPS for all users.” That thought pervades the enterprise PNT Architecture, beginning with its foundational recommendation (that GPS remain the cornerstone) and extending through many of the 18 other recommendations which follow. In the Architecture, however, we put a slightly different twist on the objective of GPS integration.
We recognize that, while GPS service can be improved by increases in signal power, possible additional signal frequencies, and a larger constellation, GPS itself can never become “impregnable.” Rather, by integrating GPS with augmentations and complements of several different types, our objective is to create continuously available PNT of high precision and fidelity from a variety of sources without regard to which particular source(s) is/are contributing to the solution at any particular point. I like to refer to that as “cloud PNT” with a bow to the recent advancements in “cloud computing.”
Finally, with regard to eLoran, the PNT Architecture envisioned a place in 2025 for an evolved eLoran-type capability, recognizing the possible value of frequency diversity, higher power, signal penetration, carrying 2D position and precise time, all in a relatively low-cost government-provided LF/MF service. Of course, it would have had to compete with other technology alternatives, but that potential course now seems foreclosed. You make the point that the basis for eLoran is, of course, the Loran-C system whose operation was recently terminated by the Obama Administration.
The most troubling aspect of that termination was the statement in the Federal Register announcement that the DHS would continue an assessment to determine if a single, domestic system is needed as a GPS backup for critical infrastructure applications at the same time it determined that the continued operation of the viable backup represented by Loran was not necessary.
Go figure.
— Jules McNeff Editorial Advisory Board (since 1990), GPS World
The Spy
A prescient reader wrote a comment on the webpage of a recent story about the demise of Loran. See env-gpsworld-integration.kinsta.cloud/rtcm and scroll all the way down. It begins:
Tso had just installed the last of a series of innocuous-looking boxes in a field some miles to the west of New York City. . . . It, and the other 299 units like it, had a single purpose. It was so simple, and it had been handed like a gift to him by the U.S. government itself. . . . .
At the start of a new decade, let’s examine the state of the GNSS consumer market and technology. In the December 2009 issue of GPS World, I described the developments that put GPS in cell phones over the last decade. That technology revolution has brought GPS a very long way. Having come this far, we can ask that most famous of all navigation questions:
Are we there yet?
In this column, I focus on the question for the consumer segment of GNSS. Has the consumer market reached the point we expected it to be by now? Has the technology reached levels we anticipated?
The cell-phone GPS revolution began with the catalyst of U.S. E911 legislation, which mandated that when an emergency (911) call is made from a cell phone, the location of the cell phone must be provided. Among several competing location technologies, GPS proved to be the big winner, thanks to seven technology enablers: assisted GPS, massive parallel correlation, high sensitivity, coarse-time navigation, low TOW, host-based GPS, and RF-CMOS.
All of these together enable very low-cost implementation of GPS in cell phones, even phones on networks such as GSM and W-CDMA that do not have fine-time synchronization (that is, they are not precisely synchronized with the GPS system). GPS is now found in roughly 500 million phones in use today.
Four Milestones. From a consumer market perspective, we have exceeded forecasts. From a technology perspective, we have kept track with Moore’s law. Chips and receivers are cheaper than expected — because, as well as Moore’s law, we have seen greatly increased volumes and competition. Low-cost chips have not come at the expense of performance; in fact, the opposite — as chips have evolved, they have become less costly and better performing.
Small, cheap antennas have affected performance, but given the same antenna, I will demonstrate that a receiver with a single-die GPS chip costing less than $4 can outperform a $19,000 receiver.
This sounds paradoxical, even impossible — indeed many of you may be penning letters to the editor right now! But the time-to-first-fix, sensitivity, and urban-accuracy data will prove my point.
As a consequence of chip evolution, we are reaching plateaus of development for GPS-only systems. However, there remain many problems to solve, especially in urban canyons and indoors. These problems may never be solved with GPS alone, or with any single system alone. This decade will be characterized by GPS-plus; the days of GPS-only will soon recede into the past.
Don’t interpret this as a failing of GPS — quite the opposite. Because GPS-only systems have worked so well, they have found their way into half a billion cell phones, and we are boldly taking GPS to places no navigation has gone before. As we do, we start to encounter the limitations of GPS-only performance.
We will see the proliferation of GPS-plus: GPS+MEMS, GPS+Wi-Fi, GPS+NMR, and GPS+GLONASS, Compass, QZSS, and Galileo. The winners will be those with the greatest levels of integration. To paraphrase Winston Churchill, this is not the end of GPS, it is not even the beginning of the end. But it is, perhaps, the end of the beginning.
GNSS Consumer Market
For market forecasts made a few years ago, we can look at summaries provided in GNSS Markets and Applications, by Len Jacobson: a 2006 Frost & Sullivan report estimated the market for PNDs and handheld devices (not including cell phones) in 2010 would be $2.7 billion, with 8.3 million units, at an average selling price (ASP) of $325. In fact, this market today is approximately $6 billion, with 40 million units, at an ASP of $150.
Twice the Size. The consumer market, not including cell phones, is twice as big (in dollars) as forecast just a few years ago, even though prices are less than half forecast. Unit sales are more than four times forecast.
For the cell-phone market segment, in 1999 when the E911 rules were enacted in the United States, it was anticipated that A-GPS would be adopted only in fine-time (synchronized) networks, such as Verizon and Sprint CDMA. In coarse-time (non-synchronized) networks such as GSM, the expectation was that terrestrial wireless location techniques, such as time-difference-of-arrival (TDOA) and enhanced-offset-time-difference (E-OTD), would dominate. Today, only a few niches use TDOA, E-OTD is extinct, and GPS rules in coarse-time networks worldwide, including GSM in Europe and North America, and W-CDMA in Japan.
The consumer market, in particular the cell-phone market, has grown so rapidly that more receivers have been built in cell phones in the last three years than all other GPS built, ever. Today, L1 C/A-code GPS accounts for more than 99 percent of all GNSS receivers manufactured each year.
From a consumer market perspective, have we reached the point we expected to be by now?
Yes!
Not only have we arrived, we have far surpassed expectations.
GPS and Moore’s Law
Moore’s law says that for a given number of transistors, the chip size will halve every two years. Table 1 shows what this looks like in practice. For a particular class of GPS chip, the A-GPS receiver with massive parallel correlation, it shows release dates of different generations of these chips, and the technology process, which is the linear dimension of a single gate on the silicon die. As this dimension reduces to 70 percent of the previous value, the 2-dimensonal chip size reduces by 2 times. You can see Moore’s law in action here: approximately every two years, the technology process moves to the next level, and the chip size reduces by 2X. People are now talking about GPS chips in 45 nanometers, the next step.
For a comparison, consider the Broadcom BCM 4751 chip, designed for cell phones. This chip is 2.9 X 3.1 millimeters, the size of the letter B on this page. This is a single-die host-based GPS/SBAS receiver, including RF front end, low-noise amplifier, baseband, and power management unit. Ten iterations of Moore’s law have passed in the last 20 years. The same chip, had it been built 20 years ago, would have been 210 times (a thousand times) bigger.
There were never chips that big. GPS chips aren’t just getting smaller with Moore’s law, they are getting vastly more complex and more capable.
Performance
At an elemental level, a GPS receiver does just three things: it starts, it tracks weak signals, and it computes position, velocity, and time. Strip away the obfuscating details, and performance may be summed up by: how fast, how sensitive, how accurate.
Since the 1990s, time to first fix ( TTFF) and sensitivity have improved dramatically, thanks to the seven technology enablers discussed earlier. TTFF for assisted cold starts, or unassisted warm starts, is now as good as one second, even without fine-time. This is a 45X improvement on typical GPS performance of the 1990s. Sensitivity increased roughly 30X (to -150 dBm) in 1998, then another 10X, (to -160 dBm) in 2006, and perhaps another three times to date, for a total of almost 1,000X extra sensitivity.
What about accuracy?
Some perceive low-cost chips as synonymous with low accuracy. This is not true. It is true that small, cheap antennas reduce accuracy; but given the same antennas, the lowest cost receivers on the market today will outperform the most expensive in typical environments where cell phones are used. The following figures show data to prove this point.
First we connect one of the smallest, lowest cost GPS receivers t
o one of the best antennas, a choke ring, on a rooftop with a clear view of the sky. Figure 1 shows the scatter of positions. The blue circle shows the median distribution, which is 0.9 meters for this dataset of 2000 fixes.
FIGURE 1a. Low-cost GPS with large, rooftop antenna.FIGURE 1b. Survey-grade GPS with large, rooftop antenna.
The adjacent plot shows the positions obtained from a $19,000 survey-grade GPS receiver, connected to the same antenna. The survey-grade GPS, with a median distribution of 0.3 meters, shows a 60-centimeter advantage over the cell-phone GPS, or maybe a 3X advantage depending on how you look at it. But don’t get too hung up on this result, because this is neither the typical consumer scenario (on a rooftop with choke-ring antenna), nor the main challenge facing us today.
Next we look at the accuracy achieved with a more typical consumer antenna, in a more typical environment. Figure 2 shows the positions obtained in downtown San Jose with an active patch antenna, such as found in PNDs. San Jose is a fairly typical U.S. city, not the hardest place to use GPS, but not the easiest either. Lightstone Alley, adjacent to tall buildings, is only five meters wide.
FIGURE 2. Performance of cell-phone GPS (white) versus truth-reference system (blue). Median accuracy 4.4 meters, 67 percent 5.6 meters, 95 percent 11.2 meters.
To evaluate accuracy we used a truth-reference system combining GPS and a tactical-grade IMU with ring laser gyro to produce the blue dots on the figure. The white dots are the low-cost GPS positions. Most of the time, the white dots appear to be on top of the blue, but occasionally you see some separation, and there the red lines show the horizontal error. The median horizontal error is 4.4 meters.
Figure 3 shows the comparison of low- and high-cost receivers, with the survey-grade receiver connected to the same patch antenna as the cell-phone GPS. There are many position gaps from the survey-grade receiver, and the position walks around when the vehicle is stationary (at the intersections, bottom left and top of the figure). This is because of the weak signals available in the urban environment. But don’t get too hung up on this result either, since we are still not at the real challenge of consumer GPS: location in severe urban canyons, such as San Francisco, New York, Chicago, Shanghai, Taipei, Shinjuku, and similar. In these, typically, only one or two GPS satellites can be seen directly. Other satellites may be tracked, but only by observing purely reflected signals. This is not classic GPS multipath, the combination of a direct and reflected signal; instead this is the combination of nothing but reflected signals. The direct signals are usually completely blocked by many buildings, and are not observable at all. So the whole premise of GPS — observing range from time of flight — breaks down, and it is very difficult to get good accuracy.
FIGURE 3. Comparison of cell-phone (left) and survey (right) receivers, both with patch antenna
Figure 4 compares the cell-phone GPS with the survey-grade GPS, connected to the same small antenna, under such circumstances in San Francisco’s Financial District. There are no fixes at all from the survey-grade receiver. Why?
FIGURE 4. Cell-phone (left) and survey (right) receivers, in severe urban canyon
In Montgomery Street, there was only one directly visible satellite, with a signal strength of -132 dBm. All the other satellites were at -140 dBm or weaker, and traditional GPS receivers cannot acquire signals at this level. Hence the only receivers that work in this environment are modern high-sensitivity receivers most commonly found in cell phones.
You can see that the move to lower-cost receivers has not come at the expense of performance. In fact, the opposite: TTFF and sensitivity have improved dramatically, while accuracy has not been compromised, and is in fact much better in urban environments than legacy receivers, and even modern survey-grade receivers.
But are we there yet?
Although the consumer GPS market has irrefutably arrived, from a technical perspective the answer is more nuanced. Consumer GPS technology has made tremendous leaps forward. But precisely because of these improvements, we are taking GPS where it was never expected to go. It is no longer enough for GPS to work indoors (which it can). The demand is now for it to work as well as if it were outdoors (which, presently, it cannot).
Performance improvements seen with GPS-only will almost certainly not continue at the recent rate. We do not anticipate yet another 45X improvement in TTFF, or another 30 dB of sensitivity, for GPS alone. However, we do expect order-of-magnitude performance increases with the addition of other technologies. Figure 5 shows data from a TomTom 950, a GPS+MEMS containing the same GPS chip used in the earlier tests, MEMS accelerometers, and MEMS rate gyros. When tightly integrated and tested in the same deep urban canyons of San Francisco, the effect on position is good: median accuracy improved by 30 percent, worst-case errors are more than halved. But the result on heading accuracy is especially dramatic.
FIGURE 5. PND position accuracy (left), and heading accuracy (right), San Francisco
The bar graph shows the worst-case heading accuracy in each street. With GPS-only (red), the worst-case error is around 45 degrees, a familiar result to anyone who has used any GPS-only device in a similar environment: sooner or later the map will veer erroneously. However, with the integration of the MEMS rate gyros (blue), the worst-case heading errors drop to around 3 degrees, a 15X improvement in a key metric, similar to the improvements of the last decade, but now thanks to the effect of GPS-plus.
We will soon see GPS-plus many other technologies: Wi-Fi, NMR/MRL (power measurements from GSM and 3G phones), and of course GPS+GLONASS, Compass, QZSS, and Galileo. Because many mobile devices now include GPS, Wi-Fi, and 3G, there is a natural path for the evolution of GPS technology to include Wi-Fi and MRL measurements.
There is a also natural trend to source different radios from the same chip supplier. After all, why would you wish to undertake a do-it-yourself effort at removing co-existence issues in different radios, when a chip supplier has already done it for you?
Looking forward, it is very likely that this new decade will be characterized by GPS-plus other technologies, and the winners will be those with the greatest levels of integration.
Frank van Diggelen is senior technical director of GPS systems and chief navigation officer for Broadcom Corporation. He holds more than 45 U.S. patents, has a Ph.D. in electrical engineering from Cambridge University, and is the author of A-GPS: Assisted GPS, GNSS & SBAS.
FIGURE 2. Trapezoidal PN (1 Mcps) waveform pulse and its time derivative with a 0.1-microsecond rise time.![FIGURE 3. Discriminator channel, d[e], and (bottom) discriminator output, R[e] Rd[e], for the 1.0 Mcps PN with the optimum 0.1-microsecond reference and the 0.1-microsecond rise-time trapezoidal waveform.](https://stage.globalpositioningnews.com/wp-content/uploads/2010/05/EA-3.jpg)
