LabSat 2 now has the ability to record and replay satellite signals from the rapidly expanding Chinese navigation system, BeiDou. LabSat 2 users can now record and replay any combination of two channels from the three available constellations, GPS, GLONASS, and Beidou.
Existing LabSat 2 users can download the latest firmware (v2.0.0) and PC software (v2.6.14) to add this functionality with no cost.
There is a growing trend to include multi-constellation capability into new satellite navigation receivers, giving the end user better coverage in urban canyons, and overall improved positional accuracy, LabSat said.
There are now 14 operational Beidou satellites, and we have recorded a number of different files from Europe and China containing between 6 and 8 satellites. These scenarios are now included on the hard disk which is shipped with a LabSat 2, which can also be shipped out to existing customers on request.
The new firmware and software is now available from the Support section of the LabSat website. Follow the upgrade firmware instructions in the manual to upgrade your LabSat 2. For more information contact our LabSat Product Manager, Mark Sampson, [email protected].
Conception, Realization, Evaluation of a Seven-Element GNSS CRPA
By Frederic Leveau, Solene Boucher, Erwan Goron, and Herve Lattard
A controlled radiated pattern antenna can be an effective way to protect GPS receivers against jamming. A new CRPA, composed of seven elements, works on the E5a, E5b, E6, L2, and L1 bandwidths. This article reports on radiation pattern measurements of the array in a test facility.
Controlled radiation pattern antenna (CRPA) technique is considered to be the best GPS pre-correlation protection technique against interference. It consists of an antenna array and a processing unit that performs a phase-destructive sum of the incoming interference signals, this process being equivalent to making nulls towards interferers in the array radiation pattern.
Considering the growing Galileo system and the possible interest of the French Ministry of Defense in the Public Regulated Service (PRS) , a prospective study was undertaken to develop an array compatible with GPS M-code, Galileo PRS, and aeronautical radionavigation signals in the E5 bandwidth. The French Expertise & Procurement Defence Agency (DGA) awarded the French company SATIMO a feasibility contract to design, conceive, realize, and evaluate a circular array composed of seven elementary patch antennas (see Figure 1).
Figure 1. CRPA unit receiving satellite and jammer signals.
Product Features
SATIMO, a company specializing in R&D for antennas and in innovative antenna test ranges, has since developed this GPS-Galileo CRPA antenna, shown below.
New CRPA developed by SATIMO.
The CRPA consists of seven elementary patches covering E5a, E5b, L2, E6, L2, and L1 frequency bandwidths, using microstrip multilayer technology. Each element is housed in a 9-centimeter (diameter) by 2-centimeter (height) radome, connector excluded. In that volume, a space provision has been reserved to include a low-noise amplifier (LNA) and two filters for a sharp out-of-band rejection. As a consequence, it is possible to configure three types of arrays: passive without filters, passive with two passband filters, and finally active (including a LNA, with a gain > 26dB, NF<0.9dB) with two passband filters. The maximum gain levels in these configurations are from 3.6 dBi to 29.8 dBi. For radiation patterns, see Figure 2.
The design of the single element has been optimized to control the deviations of each patch antenna when included in a seven-element array.
To limit mutual coupling with respect to the array dimensions, the distance between the elements’ phase centers has been chosen close to 0.7 λ at L1 frequency. This value results in a 36.5-centimeter (diameter) array. The standalone antenna and the CRPA antenna have been validated through an environmental testing campaign.
Product Development
The usual iterative tuning and the optimization process for prototyping have been performed on SATIMO’s arch test range. This test facility indeed significantly reduces the time required to characterize the antenna-under-test (AUT) radiation pattern, in comparison with classical anechoic chamber test facilities.
More precisely, the arch test range instantaneously scans the field in one whole site angle cross-section plane, whereas the legacy systems mechanically scan the same cross-section plane by rotating the AUT for each incremental angle value. The spatial sampling of the near-field radiated by the AUT, thanks to a large number of probes along the arch surrounding it, enables a significant savings in time. The near-field results in the current plane can be displayed in real-time on a computer screen. Then, the rotation of AUT around its axis is automatically controlled by the measurement system, and a new acquisition is performed for each new cross-section plane. A Fourier transform computation is eventually applied to the 3D near-field to get the far-field radiation pattern.
The radiating characterization of the CRPA has been performed with a SATIMO SG24 system. With such a system, we have measured the complete 3D radiation patterns of each single element in less than 40 minutes per antenna.
Evaluation
The evaluation of the CRPA array was performed with this test bed in SATIMO’s facility (see photos below). The process begain with measuring an element alone on a ground plane, in order to extract the gain, the axial ratio, the aperture angle, the matching values, and every feature that defines a fixed-radiation pattern antenna. The evaluation secondly consisted of characterizing the array, that is, extracting the gain and the phase of each element in the array, with respect to a reference element. To implement such a reference anytime during the near-field acquisition process, the arch test range (Figure 3) is very powerful, because all the probes constantly point at the center of the array, despite AUT’s motions. On the contrary, the need for such a reference makes measurements difficult in anechoic chambers, which often require canceling out misalignments, thanks to specific motions that must be taken into account in the computations.
CRPA in measurements.CRPA in measurements.Figure 3. Arch test range working principle.
Uses
Functional tests are another important part of the CRPA unit evaluation. Usually, two kind of tests can be conducted: outdoors or in anechoic chamber.
Classical Tests. DGA plans to perform outdoor test campaigns by utilizing an array placed on the roof of an all-terrain vehicle (see photo). The array will be connected to a CRPA GPS processing unit and to a receiver in the vehicle. Some interferers will be located along the trajectory of the vehicle, according to various scenarios defining their waveforms and their power levels. The CRPA capability to reject those interferers can then be assessed. These kinds of outdoor tests naturally suit CRPA’s processing unit and array characterization, as they involve radiated GPS and interfering signals. However, these kinds of tests are not reproducible and are quite complicated to set up.
Outdoor jamming test campaign.
Some tests in anechoic chambers could be an alternative in order to obtain reproducible test results, but in that case, transmitting GPS constellation signals indoor becomes a challenge. An option could be the use of a GPS signal simulator, but this means a unique direction of arrival of GPS signals. Moreover, no dynamic trajectory could be done.
New Test Bed. DGA recently acquired a test bed, developed by INEO Defense, that enables evaluating CRPA units in conducted mode, for example. There is no longer a need to radiate either GPS signals or interfering signals. The purpose of this test bed, called BAnc de Caractérisation des Antennes Réseaux Antibrouillage (BACARA), or test bed to characterize anti-jamming antenna arrays (Figure 4 and Figure 5), is to replace the array and simulate its GPS and jamming environment. This means that it is able to create elementary antenna phase delays and gains resulting from the array geometry, by using finite impulse response (FIR) filters (Figure 6). This is the reason why this test bed must be fed with the array phase and gain measurement results obtained with the arch test range.
Figure 4. BACARA test bed.Figure 5. BACARA working principle.Figure 6. BACARA working principle.
Alternatively, these results can be obtained with traditional anechoic chamber measurements. 10 channels of a multi-channel GPS simulator, each one matched with a satellite, are used by the test bed. Thus, BACARA coherently sums GPS constellation simulator output channels and interfering signals, so as to accurately simulate the array’s behavior in the laboratory. As a result, for any CRPA processing unit, it is possible to compare the array’s impact on a processing unit with an ideal array being composed of perfect elementary antennas.
Unfortunately, BACARA currently operates on L1 or L2, but not on the E6 and E5 bandwidths. On the other hand, this test bed is able to simulate dynamic trajectories, with the mobile positions and attitudes. Up to 10 internal jammers with various waveforms can be set up, and their power levels over time are computed by software like Warfare or Matlab. A numerical calibration allows some transparency of the test bed for CRPA units under test.
Figure 7. BACARA graphical user interface.Figure 8. Examples of available simulated array geometry.
Conclusion
SATIMO, a company specializing in electromagnetic field measurements in the microwave frequency range and part of the Microwave Vision Group, has developed an array for the reception of M-code, PRS, and aeronautical radionavigation signals. This antenna array has been fully evaluated and qualified through electrical and environmental tests. The measurement methods have enabled the company to demonstrate the feasibility of the performances expected. Functional evaluations restricted to GPS are still under way. To do so, DGA will utilize its complementary outdoor and indoor test means, especially its laboratory test bed BACARA, as a tool to precisely evaluate GPS CRPA units.
Frederic Leveau works at the French MoD (DGA Information Superiority) as a radionavigation expert. His main interests are Galileo PRS prospective studies and developments and the integration of CRPA systems within French platforms.
Solene Boucher works at the French MoD (DGA Information Superiority) as a radionavigation expert. Her main interests are Galileo PRS prospective studies and developments. She is also responsible for the test bed BACARA.
Erwan Goron is an engineer at SATIMO Industries (Microwave Vision Group). His main activity is antenna conception.
Herve Lattard is an engineer at SATIMO Industries (Microwave Vision Group). His main activity is antenna conception.
Economically, the System Differs Significantly from Its GNSS Cousins
John W. Lavrakas
In May 2007, I authored an article in GPS World looking ten years into the future and envisioning how the GNSS field would operate at that then-distant time. Reviewing my assessments, I see that I was both accurate and wide of the mark with my predictions.
The prediction that has proved accurate was that the GNSS world would be hybrid, with no one system as the sole provider of satellite-based positioning and timing services. This was hardly a risky prediction. Most in the GNSS community would have come to the same assessment.
But what I did not see coming were the advances China would take with its BeiDou program. My original assessment was based on three GNSSs only: GPS, GLONASS, and Galileo, and did not include BeiDou.
When I did my analysis in 2006, China was pretty quiet on BeiDou: no technical descriptions, no interface control document (ICD); no presentations at conferences of the Institute of Navigation. What little we knew about BeiDou was that it was a limited system, offering at best a regional solution. The original design was an active system using geosynchronous satellites, requiring each remote unit to request position from the satellite, which was calculated and sent back to the remote station.
How things have changed.
Since 2007, China has reshaped the BeiDou concept into a full-fledged modern GNSS, offering CDMA codes, navigation messages, and data rates comparable to GPS and Galileo — and lots of satellites. The ICD states in section 3.1, “When fully deployed, the space constellation of BDS consists of five geostationary Earth-orbit (GEO) satellites, twenty-seven medium Earth-orbit (MEO) satellites, and three inclined geosynchronous satellite orbit (IGSO) satellites.” No dates are provided, however, regarding attaining these numbers. So the BeiDou system promises to be on par with the other GNSSs.
Why does this matter?
While technically the BeiDou system resembles its cousins, economically it presents quite a different animal. Unlike other nations offering GNSS, China has a huge capacity for manufacturing at low cost. Considering this situation from a business perspective, a possible scenario could be that China offers GNSS chipsets that operate with BeiDou (either solely or as a hybrid with another GNSS)at extremely low prices. In doing so, China could corner the market for general purpose LBS applications (setting aside specialty receivers, such as for surveying and aviation applications). The price point would be so attractive that LBS services would employ Chinese devices in preference to the GPS ones, much like consumers purchase television sets: most come from China, and none are made in the United States any more.
China offers something, then, in this scenario that neither Russia, Europe, nor the United States can currently match. This may not be the scenario that eventually occurs, but it is possible. Other factors such as local terrestrial PNT solutions and dual-frequency improvements will come into play, but what I have described is one possible scenario. While the signal is free, the equipment is not, and when we are talking about a billion or more installations, cost is going to be a big driver.
Am I going out on a limb and saying that BeiDou will be the system of choice in another ten years or so? No, I would not go this far.
But I do say that serious competition for GNSS users (read “market share”) is now in play. Further, it is important for each GNSS operator to recognize this as they consider the services and features they choose to offer, and the impact these have in capturing their share of the market. GNSS providers now must factor the business aspect of their services as much as the technical, scientific, or safety of life. The U.S. government, for one, has gotten a bit complacent in upgrading GPS services to meet user needs, operating from a basis that it is the only GNSS on the block. It could wake up one day and find this no longer to be the case.
John Lavrakas is president of Advanced Research Corporation, where he provides consulting services on satellite navigation and fishery information systems. He has spent 32 years in GPS, supporting development of the GPS Control Segment, GPS user equipment, GPS performance analysis capabilities, and developing and marketing location-based systems. He is past president of the Institute of Navigation and an ION Fellow.
A Case History Using the New Galileo E6-B/C Signal
By Sergei Yudanov, JAVAD GNSS
A method of decoding an unknown pseudorandom noise code uses a conventional GNSS antenna and receiver with modified firmware. The method was verified using the signals from the Galileo In-Orbit Validation satellites.
Decoding an unknown GNSS pseudorandom noise (PRN) code can be rather easily done using a high-gain steerable dish antenna as was used, for example, in determine the BeiDou-M1 broadcast codes before they were publicly announced. The signal-to-noise ratio within one chip of the code is sufficient to determine its sign. This article describes a method of getting this information using a conventional GNSS antenna and receiver with modified firmware. The method was verified using the signals from the Galileo In-Orbit Validation (IOV) satellites. In spite of the fact that only pilot signal decoding seems to be possible at first glance, it is shown that in practice data signals can also be decoded.
Concept
The idea is to do coherent accumulation of each chip of an unknown signal during a rather long time interval. The interval may be as long as a full satellite pass; for medium Earth orbits, this could be up to six hours. One of the receiver’s channels is configured in the same way as for signal tracking. The I and Q signal components are accumulated during one chip length in the digital signal processor, and these values are added to an array cell, referenced by chip number, by the processor. Only a limited amount of information need be known about the signal: its RF frequency; the expected chip rate; the expected total code length; and the modulation method.
The decoding of binary-phase-shift-keying (BPSK) signals (as most often used) is the subject of this article. It appears that the decoding of more complicated signals is possible too, but this should be proved. A limitation of this method (in common with that of the dish method) is the maximum total code length that can be handled: for lengths greater than one second and bitrates higher than 10,000 kilobits per second, the receiver’s resources may not be sufficient to deal with the signal.
Reconstructing the Signal’s Phase
This method requires coherency. During the full accumulation period, the phase difference between the real signal phase and the phase of the signal generated by the receiver’s channel should be much less than one cycle of the carrier frequency. Depending on the GNSS’s available signals, different approaches may be used. The simplest case is reconstruction of a third signal while two other signals on different frequencies are of known structure and can be tracked.
The main (and possibly the only significant) disturbing factor is the ionosphere. The ionospheric delay (or, more correctly, the variation of ionospheric delay) is calculated using the two known tracked signals, then the phase of the third signal, as affected by the ionosphere, is predicted.
The final formula (the calculations are trivial and are widely available in the literature) is:
where:
φ1 , f1 are the phase and frequency of the first signal in cycles and Hz, respectively
φ2 , f2 are the phase and frequency of the second signal in cycles and Hz, respectively
φ3 , f3 are the phase and frequency of the third signal in cycles and Hz, respectively.
It was confirmed that for all pass periods (elevation angles less than 10 degrees were not tested), the difference between the calculated phase and real phase was always less than one-tenth of a cycle. GPS Block IIF satellites PRN 1 and PRN 25 were used to prove this: the L1 C/A-code and L5 signals were used as the first and second signals, with the L2C signal as the third unknown.
If two known signals are not available, and the ionospheric delay cannot be precisely calculated, it is theoretically possible to obtain an estimate of the delay from one or more neighboring satellites with two signals available. Calculations and estimations should be carried out to investigate the expected precision.
The Experiment
The Galileo E6-B/C signal as currently transmitted by the IOV satellites was selected for the experiment, as its structure has not been published. The E6 signal has three components: E6-A, E6-B and E6-C. The E6-A component is part of the Galileo Public Regulated Service, while the two other components will serve the Galileo Commercial Service. The E6-B component carries a data signal, while the E6-C component is a pilot signal.
From open sources, it is known that the carrier frequency of the E6 signal is 1278.75 MHz and that the E6-B and E6-C components use BPSK modulation at 5,115 chips per millisecond with a primary code length of one millisecond. E6-B’s data rate is 1,000 bits per second and the total length of the pilot code is 100 milliseconds (a secondary code of 100 bits over 100 milliseconds is also present in the E6-C signal, which aids in signal acquisition).
A slightly modified commercial high-precision multi-GNSS receiver, with the E6 band and without the GLONASS L2 band, was used for this experiment. The receiver was connected to a conventional GNSS antenna, placed on a roof and was configured as described above. The E1 signal was used as the first signal and E5a as the second signal. The E6 code tracking (using 5,115 chip values of zero) was 100 percent guided from the E1 code tracking (the changing of the code delay in the ionosphere was ignored). The E6 phase was guided from E1 and E5a using the above equation. Two arrays for 511,500 I and Q samples were organized in firmware. The integration period was set to one chip (200 nanoseconds).
Galileo IOV satellite PRN 11 (also variously known as E11, ProtoFlight Model and GSAT0101) was used initially, and the experiment started when the satellite’s elevation angle was about 60 degrees and lasted for only about 30 minutes. Then the I and Q vectors were downloaded to a PC and analyzed.
Decoding of Pilot Signal (E6-C)
Decoding of the pilot signal is made under the assumption that any possible influence of the data signal is small because the number of ones and zeros of E6-B in each of 511,500 chips of the 100-millisecond integration interval is about the same. First, the secondary code was obtained. Figure 1 shows the correlation of the first 5,115 chips with 5,115 chips shifted by 0 to 511,500 chips. Because the initial phase of the E6 signal is unknown, two hypotheses for computing the amplitude or signal level were checked: [A] = [I] + [Q] and [A] = [I] – [Q], and the combination with the higher correlation value was selected for all further analysis.
Figure 1. Un-normalized autocorrelation of E6-C signal chips.
In Figure 1, the secondary code is highly visible: we see a sequence of 100 positive and negative correlation peaks (11100000001111 …; interpreting the negative peaks as zeros).This code is the exact complement (all bits reversed) of the published E5a pilot secondary code for this satellite. More will be said about the derived codes and their complements later. It appears that, for all of the IOV satellites, the E6-C secondary codes are the same as the E5a secondary codes.
After obtaining the secondary code, it is possible to coherently add all 100 milliseconds of the integration interval with the secondary code sign to increase the energy in each chip by 100 times. Proceeding, we now have 5,115 chips of the pilot signal — the E6-C primary code.
To understand the correctness of the procedure and to check its results, we need to confirm that there is enough signal energy in each chip. To this end, a histogram of the pilot signal chip amplitudes can be plotted (see Figure 2). We see that there is nothing in the middle of the plot. This means that all 5,115 chips are correct, and there is no chance that even one bit is wrong.
Figure 2. Histogram of pilot signal chip amplitude in arbitrary units.
But there is one effect that seems strange at first glance: instead of two peaks we have four (two near each other). We will shortly see that this phenomenon results from the influence of the E6-B data signal and it may be decoded also.
Decoding the Data Signal
The presence of four peaks in the histogram of Figure 2 was not understood initially, so a plot of all 511,500 signal code chips was made (see Figure 3).
Interestingly, each millisecond of the signal has its own distribution, and milliseconds can be found where the distribution is close to that when two signals with the same chip rate are present. In this case, there should be three peaks in the energy (signal strength) spectrum: –2E, 0, and +2E, where E is the energy of one signal (assuming the B and C signals have the same strength).
Figure 3. Plot of 511,500 signal code chip amplitudes in arbitrary units.
One such time interval (starting at millisecond 92 and ending at millisecond 97) is shown in Figure 4. The middle of the plot (milliseconds 93 to 96) shows the described behavior. Figure 5 is a histogram of signal code chip amplitude for the signal from milliseconds 93 to 96.
Figure 4. Plot of signal code chip amplitude in arbitrary units from milliseconds 93 to 96.
Then we collect all such samples (milliseconds) with the same data sign together to increase the signal level. Finally, 5,115 values are obtained. Their distribution is shown in Figure 6.
The central peak is divided into two peaks (because of the presence of the pilot signal), but a gap between the central and side peaks (unlike the case of Figure 5) is achieved. This allows us to get the correct sign of all data signal chips. Subtracting the already known pilot signal chips, we get the 5,115 chips of the data signal — the E6-B primary code. This method works when there are at least some samples (milliseconds) where the number of chips with the same data bit in the data signal is significantly more than half.
Figure 5. Histogram of signal code chip amplitude.Figure 6. Histogram of the signed sum of milliseconds chip amplitude with a noticeable presence of the data signal.
Proving the Codes
The experimentally determined E6-B and E6-C primary codes and the E6-C secondary codes for all four IOVsatellites (PRNs 11, 12, 19, and 20) were put in the receiver firmware. The receiver was then able to autonomously track the E6-B and E6-C signals of the satellites.
Initial decoding of E6-B navigation data has been performed. It appears that the data has the same preamble (the 16-bit synchronization word) as that given for the E6-B signal in the GIOVE Interface Control Document (ICD). Convolutional encoding for forward error correction is applied as described in the Galileo Open Service ICD, and 24-bit cyclic redundancy check error detection (CRC-24) is used. At the time of the analysis, all four IOV satellites transmitted the same constant navigation data message.
Plots of PRN 11 E6 signal tracking are shown in Figure 7 and in Figure 8. The determined codes may be found at env-gpsworld-integration.kinsta.cloud/galileo-E6-codes. Some of these codes may be the exact complement of the official codes since the code-determination technique has a one-half cycle carrier-phase ambiguity resulting in an initial chip value ambiguity. But from the point of view of receiver tracking, this is immaterial.
Figure 7. Signal-to-noise-density ratio of E1 (red), E5a (magenta), E5b (blue), and E6 (green) code tracking of Galileo IOV satellite PRN 11 on December 21–22, 2012.Figure 8. Pseudorange minus carrier phase (in units of meters) of E1 (red), E5a (magenta), E5b (blue), and E6 (green) code tracking of Galileo IOV satellite PRN 11 on December 21–22, 2012.
Acknowledgments
Special thanks to JAVAD GNSS’s DSP system developers. The system is flexible so it allows us to do tricks like setting the integration period to one chip, and powerful enough to be able to do required jobs within a 200-nanosecond cycle. This article was prepared for publication by Richard Langley.
Manufacturers
A JAVAD GNSS TRE-G3T-E OEM receiver, a modification of the TRE-G3T receiver, was used in the experiment, connected to a conventional JAVAD GNSS antenna. Plots of E6 code tracking of all four IOV satellites may be found on the company’s website.
Sergei Yudanov is a senior firmware developer at JAVAD GNSS, Moscow.
Off-the-Shelf Antennas for Controlled-Reception-Pattern Antenna Arrays
By Yu-Hsuan Chen, Sherman Lo, Dennis M. Akos, David S. De Lorenzo, and Per Enge
INNOVATION INSIGHTS by Richard Langley
THE ANTENNA IS A CRITICAL COMPONENT OF ANY GNSS RECEIVING EQUIPMENT. It must be carefully designed for the frequencies and structures of the signals to be acquired and tracked. Important antenna properties include polarization, frequency coverage, phase-center stability, multipath suppression, the antenna’s impact on receiver sensitivity, reception or gain pattern, and interference handling. While all of these affect an antenna’s performance, let’s just look at the last two here.
The gain pattern of an antenna is the spatial variation of the gain, or ratio of the power delivered by the antenna for a signal arriving from a particular direction compared to that delivered by a hypothetical isotropic reference antenna. Typically, for GNSS antennas, the reference antenna is also circularly polarized and the gain is then expressed in dBic units.
An antenna may have a gain pattern with a narrow central lobe or beam if it is used for communications between two fixed locations or if the antenna can be physically steered to point in the direction of a particular transmitter. GNSS signals, however, arrive from many directions simultaneously, and so most GNSS receiving antennas tend to be omni-directional in azimuth with a gain roll-off from the antenna boresight to the horizon.
While such an antenna is satisfactory for many applications, it is susceptible to accidental or deliberate interference from signals arriving from directions other than those of GNSS signals. Interference effects could be minimized if the gain pattern could be adjusted to null-out the interfering signals or to peak the gain in the directions of all legitimate signals. Such a controlled-reception-pattern antenna (CRPA) can be constructed using an array of antenna elements, each one being a patch antenna, say, with the signals from the elements combined before feeding them to the receiver. The gain pattern of the array can then be manipulated by electronically adjusting the phase relationship between the elements before the signals are combined. However, an alternative approach is to feed the signals from each element to separate banks of tracking channels in the receiver and form a beam-steering vector based on the double-difference carrier-phase measurements from pairs of elements that is subsequently used to weight the signals from the elements before they are processed to obtain a position solution. In this month’s column, we learn how commercial off-the-shelf antennas and a software-defined receiver can be used to design and test such CRPA arrays.
“Innovation” features discussions about advances in GPS technology, its applications, and the fundamentals of GPS positioning. The column is coordinated by Richard Langley, Department of Geodesy and Geomatics Engineering, University of New Brunswick. To contact him with topic ideas, email him at lang @ unb.ca.
Signals from global navigation satellite systems are relatively weak and thus vulnerable to deliberate or unintentional interference. An electronically steered antenna array system provides an effective approach to mitigate interference by controlling the reception pattern and steering the system’s beams or nulls. As a result, so-called controlled-reception-pattern-antenna (CRPA) arrays have been deployed by organizations such as the U.S. Department of Defense, which seeks high levels of interference rejection.
Our efforts have focused on developing a commercially viable CRPA system using commercial off-the-shelf (COTS) components to support the needs of Federal Aviation Administration (FAA) alternative position navigation and timing (APNT) efforts. In 2010, we implemented a seven-element, two-bit-resolution, single-beam and real-time CRPA software receiver. In 2011, the receiver was upgraded to support all-in-view, 16-bit-resolution with four elements.
Even though we can implement these CRPA software receivers in real time, the performance of anti-interference is highly dependent on the antenna array layout and characteristics of the antenna elements. Our beamforming approach allows us to use several COTS antennas as an array rather than a custom-designed and fully calibrated antenna. The use of COTS antennas is important, as the goal of our effort is to develop a CRPA for commercial endeavors — specifically for robust timing for the national airspace. Hence, it is important to study the geometry layout of the individual antennas of the array to assess the layouts and to determine how antenna performance affects the array’s use.
In our work, we have developed a procedure for calculating the electrical layouts of an antenna array by differential carrier-phase positioning. When compared to the physical layout, the results of electrical layouts can be used to determine the mutual coupling effect of each combination. Using the electrical layout, the resultant gain patterns can be calculated and used to see the beamwidth and the side-lobe issue. This is important as these factors have significant effects on anti-interference performance. This study focuses on understanding the performance effects of geometry and developing a method for describing the best geometry.
We adopted three models of COTS antenna and two possible layouts for a four-element array. Then, signal collection hardware consisting of four Universal Software Radio Peripheral (USRP) software-defined radios and one host personal computer was assembled to collect array data sets for each layout/antenna combination. Our developed CRPA software receiver was used to process all data sets and output carrier-phase measurements.
In this article, we will present the pattern analysis for the two selected layouts and describe how we collected the experimental data. We’ll then show the results of calculating the electrical spacing for the layouts are compare them to the physical layouts. Lastly, we’ll show the resulting patterns, discuss the antenna mutual coupling effects, and give our conclusions.
Antenna Array Pattern Analysis
Pattern is defined as the directional strength of a radio-frequency signal viewed from the antenna. The pattern of an antenna array is the product of the isotropic array factor and the isolated element pattern. We assume that the pattern of each element is identical and only consider the isotropic array factor. FIGURE 1 shows the coordination of an antenna array. The first element is set as a reference position. The x-axis is the east direction, the y-axis is the north direction, and the z-axis is the up direction. The baseline vector of the ith antenna is given by and is the unit vector to the satellite.
Figure 1. Antenna array geometry and direction of satellite. Array elements are identified as E#1, E#2, E#3, and E#4.
The isotropic array factor is given by
(1)
where λ is wavelength, and Ai is a complex constant. Currently, we only implement a four-element-array CRPA software receiver in real time. Hence, we analyze two kinds of layout of half-wavelength four-element arrays: a symmetrical Y array and a square array. Each antenna is separated from its nearest neighbor by a half wavelength. FIGURE 2 shows photos of the two layouts. FIGURE 3 shows the physical layouts.
Figure 2. Photos of antenna arrays (left: Y array; right: square array).Figure 3A. Physical layout of antenna arrays (Y array).Figure 3B. Physical layout of antenna arrays (square array).
The antenna patterns towards an elevation angle of 90 degrees, computed using equation 1 and the design layouts, are shown in FIGURE 4. One of the key characteristics of a pattern is the beamwidth, which is defined as the angle with 3-dB loss. FIGURE 5 shows the patterns in elevation angle where the beamwidth of the Y layout is 74 degrees and 86 degrees for the square layout. A narrow beamwidth will benefit anti-interference performance particularly if the interference is close to the direction of a target satellite.
Figure 4. Patterns of antenna arrays (left: Y array; right: square array).Figure 5. Pattern beamwidths of Y and square arrays (3 dB beamwidth shown).
Specifications of COTS Antennas
Typically, the COTS antenna selection is determined by high gain and great out-of-band rejection. TABLE 1 shows the specifications of the three antenna models used in this article. These antennas are all patch antennas. The antennas are equipped with surface-acoustic-wave filters for rejecting out-of-band signals. A three-stage low noise amplifier with over 30 dB gain is also embedded in each antenna.
Table 1. Specifications of COTS antennas used.
Signal Collection Hardware and Experimental Setup
The hardware used to collect the antenna array datasets is shown in FIGURE 6 with block-diagram representation in FIGURE 7. The hardware includes a four-element antenna array, four USRP2 software radio systems and one host computer. The signal received from the COTS antenna passes to a USRP2 board equipped with a 800–2300 MHz DBSRX2 programmable mixing and down-conversion daughterboard. The individual USRP2 boards are synchronized by a 10-MHz external common clock generator and a pulse-per-second (PPS) signal. The USRP2s are controlled by the host computer running the Ubuntu distribution of Linux. The open-source GNU Radio software-defined radio block is used to configure USRP2s and collect datasets. All USRP2s are configured to collect the L1 (1575.42 MHz) signal. The signals are converted to near zero intermediate frequency (IF) and digitized to 14-bit complex outputs (I and Q).
Figure 6. Photo of the signal collection hardware.Figure 7. Block diagram of the signal collection hardware.
The sampling rate is set as 4 MHz. The host computer uses two solid state drives for storing data sets. For our study, a 64-megabytes per second data transfer rate is needed. The fast solid state drives are especially useful when using high bandwidth signals such as L5, which will require an even higher data streaming rate (80 megabytes per second per channel).
To compare the physical and electrical layouts of the antenna arrays, we set up the signal collection hardware to record six data sets for the two layouts and the three antenna models as shown in TABLE 2. All of the data sets were five minutes long to obtain enough carrier-phase measurements for positioning.
Table 2. Experimental setups.
Logging Carrier-Phase Measurements
To calculate the precise spacing between the antenna elements, hundreds of seconds of carrier-phase measurements from each element are needed. The collected data sets were provided by our in-house-developed CRPA software receiver. The receiver was developed using Visual Studio under Windows. Most of source code is programmed using C++. Assembly language is used to program the functions with high computational complexity such as correlation operations. The software architecture of the receiver is depicted in FIGURE 8. This architecture exploits four sets of 12 tracking channels in parallel to process each IF signal from an antenna element. Each channel is dedicated to tracking the signal of a single satellite. The tracking channels output carrier-phase measurements to build the steering vectors for each satellite. The Minimum Variance Distortionless Response (MVDR) algorithm was adopted for adaptively calculating the weights for beamforming. Here, there are 12 weight sets, one for each satellite in a tracking channel, for the desired directions of satellites.
Figure 8. Block diagram of the software architecture.
Using the pre-correlation beamforming approach, the weights are multiplied with IF data and summed over all elements to form 12 composite signals. These signals are then processed by composite tracking channels. Finally, positioning is performed if pseudoranges and navigation messages are obtained from these channels. FIGURE 9 is the graphical user interface (GUI) of the CRPA software receiver. It consists of the channel status of all channels, carrier-phase differences, positioning results, an east-north (EN) plot, a sky plot, a carrier-to-noise-density (C/N0) plot and the gain patterns of the array for each tracked satellite. In the figure, the CRPA software receiver is tracking 10 satellites and its positioning history is shown in the EN plot. The beamforming channels have about 6 dB more gain in C/N0 than the channels of a single element. In each pattern, the direction with highest gain corresponds to the direction of the satellite. While the CRPA software receiver is running, the carrier-phase measurements of all elements and the azimuth and elevation angle of the satellites are logged every 100 milliseconds. Each data set in Table 2 was processed by the software receiver to log the data.
Figure 9. Screenshot of the controlled-reception-pattern-antenna software-receiver graphical user interface.
Electrical Layout of Antenna Array – Procedure
The procedure of calculating the electrical layout of an antenna array is depicted in FIGURE 10. The single-difference integrated carrier phase (ICP) between the signals of an element, i, and a reference element, j, is represented as:
(2)
where rkijis differential range toward the kth satellite between the ith and jth antenna elements (a function of the baseline vector between the ith and jth elements), δLij is the cable-length difference between the ith and jth antenna elements, Nkijis the integer associated with Φkij, εkijand is the phase error. The double-difference ICP between the kth satellite and reference satellite l is represented as: (3)
The cable-length difference term is subtracted in the double difference. Since the distances between the antenna elements are close to one wavelength, equation (3) can be written as: (4)
where is the unit vector to satellite k,pij is the baseline vector between the ith and jth elements. By combining all the double-difference measurements of the ijth pair of elements, the observations equation can be represented as: (5)
From the positioning results of composite channels, the azimuth and elevation angle of satellites are used to manipulate matrix G. To solve equation (5), the LAMBDA method was adopted to give the integer vector N. Then, pij is solved by substituting Ninto equation (5). Finally, the cable-length differences are obtained by substituting the solutions of N and pij into equation (2).
This approach averages the array pattern across all satellite measurements observed during the calibration period.
Figure 10. Procedure for calculating antenna-array electrical spacing.
Electrical Layout of Antenna Array – Results
Using the procedure in the previous section, all electrical layouts of the antenna array were calculated and are shown in FIGURES 11 and 12. We aligned the vectors from element #1 to element #2 for all layouts. TABLE 3 lists the total differences between the physical and electrical layouts. For the same model of antenna, the Y layout has less difference than the square layout. And, in terms of antenna model, antenna #1 has the least difference for both Y and square layouts. We could conclude that the mutual coupling effect of the Y layout is less than that of the square layout, and that antenna #1 has the smallest mutual coupling effect among all three models of antenna for these particular elements and observations utilized.
Figure 11. Results of electrical layout using three models of antenna compared to the physical layout for the Y array.Figure 12. Results of electrical layout using three models of antenna compared to physical layout for the square array.Table 3. Total differences between physical and electrical layouts.
To compare the patterns of all calculated electrical layouts, we selected two specific directions: an elevation angle of 90 degrees and a target satellite, WAAS GEO PRN138, which was available for all data sets. The results are shown in FIGURES 13 and 14, respectively. From Figure 13, the beamwidth of the Y layout is narrower than that of the square layout for all antenna models. When compared to Figure 5, this result confirms the validity of our analysis approach. But, in Figure 14, a strong sidelobe appears at azimuth -60º in the pattern of Y layout for antenna #2. If there is some interference located in this direction, the anti-interference performance of the array will be limited. This is due to a high mutual coupling effect of antenna #2 and only can be seen after calculating the electrical layout.
Figure 13. Patterns of three models of antenna and two layouts toward an elevation angle of 90 degrees.Figure 14. Patterns of three models of antenna and two layouts toward the WAAS GEO satellite PRN138.
Conclusions
The results of our electrical layout experiment show that the Y layout has a smaller difference with respect to the physical layout than the square layout. That implies that the elements of the Y layout have less mutual coupling. For the antenna selection, arrays based on antenna model #1 showed the least difference between electrical and physical layout. And its pattern does not have a high grating lobe in a direction other than to the target satellite.
The hardware and methods used in this article can serve as a testing tool for any antenna array. Specifically, our methodology, which can be used to collect data, compare physical and electrical layouts, and assess resultant antenna gain patterns, allows us to compare the performances of different options and select the best antenna and layout combination. Results can be used to model mutual coupling and the overall effect of layout and antenna type on array gain pattern and overall CRPA capabilities. This procedure is especially important when using COTS antennas to assemble an antenna array and as we increase the number of antenna elements and the geometry possibilities of the array.
Acknowledgments
The authors gratefully acknowledge the work of Dr. Jiwon Seo in building the signal collection hardware. The authors also gratefully acknowledge the Federal Aviation Administration Cooperative Research and Development Agreement 08-G-007 for supporting this research. This article is based on the paper “A Study of Geometry and Commercial Off-The-Shelf (COTS) Antennas for Controlled Reception Pattern Antenna (CRPA) Arrays” presented at ION GNSS 2012, the 25th International Technical Meeting of the Satellite Division of The Institute of Navigation, held in Nashville, Tennessee, September 17–21, 2012.
Manufacturers
The antennas used to construct the arrays are Wi-Sys Communications Inc., now PCTEL, Inc. models WS3978 and WS3997 and PCTEL, Inc. model 3978D-HR. The equipment used to collect data sets includes Ettus Research LLC model USRP2 software-defined radios and associated DBSRX2 daughterboards.
Yu-Hsuan Chen is a postdoctoral scholar in the GNSS Research Laboratory at Stanford University, Stanford, California.
Sherman Lo is a senior research engineer at the Stanford GNSS Research Laboratory.
Dennis M. Akos is an associate professor with the Aerospace Engineering Science Department in the University of Colorado at Boulder with visiting appointments at Luleå Technical University, Sweden, and Stanford University.
David S. De Lorenzo is a principal research engineer at Polaris Wireless, Mountain View, California, and a consulting research associate to the Stanford GNSS Research Laboratory.
Per Enge is a professor of aeronautics and astronautics at Stanford University, where he is the Kleiner-Perkins Professor in the School of Engineering. He directs the GNSS Research Laboratory.
FURTHER READING
• Authors’ Publications
“A Study of Geometry and Commercial Off-The-Shelf (COTS) Antennas for Controlled Reception Pattern Antenna (CRPA) Arrays” by Y.-H. Chen in Proceedings of ION GNSS 2012, the 25th International Technical Meeting of The Institute of Navigation, Nashville, Tennessee, September 17–21, 2012, pp. 907–914 (ION Student Paper Award winner).
“A Real-Time Capable Software-Defined Receiver Using GPU for Adaptive Anti-Jam GPS Sensors” by J. Seo, Y.-H. Chen, D.S. De Lorenzo, S. Lo, P. Enge, D. Akos, and J. Lee in Sensors, Vol. 11, No. 9, 2011, pp. 8966–8991, doi: 10.3390/s110908966.
“Real-Time Software Receiver for GPS Controlled Reception Pattern Array Processing” by Y.-H. Chen, D.S. De Lorenzo, J. Seo, S. Lo, J.-C. Juang, P. Enge, and D.M. Akos in Proceedings of ION GNSS 2010, the 23rd International Technical Meeting of The Institute of Navigation, Portland, Oregon, September 21–24, 2010, pp. 1932–1941.
“A GNSS Software Receiver Approach for the Processing of Intermittent Data” by Y.-H. Chen and J.-C. Juang in Proceedings of ION GNSS 2007, the 20th International Technical Meeting of The Institute of Navigation, Fort Worth, Texas, September 25–28, 2007, pp. 2772–2777.
• Controlled-Reception-Pattern Antenna Arrays
“Anti-Jam Protection by Antenna: Conception, Realization, Evaluation of a Seven-Element GNSS CRPA” by F. Leveau, S. Boucher, E. Goron, and H. Lattard in GPS World, Vol. 24, No. 2, February 2013, pp. 30–33.
“Development of Robust Safety-of-Life Navigation Receivers” by M.V.T. Heckler, M. Cuntz, A. Konovaltsev, L.A. Greda, A. Dreher, and M. Meurer in IEEE Transactions on Microwave Theory and Techniques, Vol. 59, No. 4, April 2011, pp. 998–1005, doi: 10.1109/TMTT.2010.2103090.
Phased Array Antennas, 2nd Edition, by R. C. Hansen, published by John Wiley & Sons, Inc., Hoboken, New Jersey, 2009.
• Antenna Principles
“Selecting the Right GNSS Antenna” by G. Ryley in GPS World, Vol. 24, No. 2, February 2013, pp. 40–41 (in PDF of 2013 Antenna Survey.)
“A USRP2-based Reconfigurable Multi-constellation Multi-frequency GNSS Software Receiver Front End” by S. Peng and Y. Morton in GPS Solutions, Vol. 17, No. 1, January 2013, pp. 89-102.
Digital Satellite Navigation and Geophysics: A Practical Guide with GNSS Signal Simulator and Receiver Laboratory by I.G. Petrovski and T. Tsujii with foreword by R.B. Langley, published by Cambridge University Press, Cambridge, U.K., 2012.
“A Real-Time Software Receiver for the GPS and Galileo L1 Signals” by B.M. Ledvina, M.L. Psiaki, T.E. Humphreys, S.P. Powell, and P.M. Kintner, Jr. in Proceedings of ION GNSS 2006, the 19th International Technical Meeting of The Institute of Navigation, Fort Worth, Texas, September 26–29, 2006, pp. 2321–2333.
NOAA’s National Geodetic Survey (NGS) is conducting a 12-year project, called Gravity for the Redefinition of the American Vertical Datum (GRAV-D), to redefine the vertical datum of the United States by flying airborne gravity missions. The accuracy of the resulting vertical datum depends directly on the quality of the aircraft’s GNSS position solutions.
In August 2010, NGS issued a Kinematic GPS Challenge to seek community input on the best practices for processing this large positioning data volume. Ten international groups answered the call, submitting 16 different position solutions calculated with a variety of software and techniques. However, the majority of solutions were corrupted by a characteristic “sawtooth” pattern which was tracked back to the aircraft receiver used in the initial challenge; for this challenge reissue, a second onboard GNSS receiver is used. Also in this new call for participation, inertial measurement unit (IMU) data are made available for joint GPS+IMU processing.
“To further facilitate our software and method development, we invite interested researchers and practitioners to compute and submit solutions from samples of actual GRAV-D data,” said Gerry Mader and Theresa Diehl, NGS, in an invitation email. “In this new call, NGS requests that all participants submit a GPS-only solution utilizing the new aircraft GPS data. For those able to process with IMU data, we request additional submission of a second IMU+GPS solution. NGS would like to receive all solutions by April 1, 2013.
“This is a strictly voluntary exercise for those interested in such a comparison and we will share our results with the participants. We are also interested in possibly co-authoring a publication with the participants on the topic if results are significant.”
Detailed information on the challenge is available here:
Those interested in participating should read through the PDF (link above), then email Gerry Mader (gerald.l.mader at noaa.gov) and Theresa Diehl (theresa.diehl at noaa.gov) with any questions.
The first switch-on of a Galileo search and rescue package shows it to be working well, according to the European Space Agency. Its activation begins a major expansion of the space-based Cospas–Sarsat network, which brings help to air and sea vessels in distress.
The second pair of Europe’s Galileo navigation satellites — launched together on October 12 last year — are the first of the constellation to host SAR search and rescue repeaters. These can pick up UHF signals from emergency beacons aboard ships and aircraft or carried by individuals, then pass them on to local authorities for rescue.
Galileo search and rescue repeater signal.
Once the satellites reached their 23,222 km-altitude orbits, a rigorous test campaign began. The turn of the SAR repeater aboard the third Galileo satellite came on January 17.
“At this stage, our main objective is to check the repeater has not been damaged by launch,” explained ESA’s Galileo SAR engineer Igor Stojkovic. “The first day was a matter of turning the repeater on and checking its temperature and power profiles were as predicted. The following day involved sending a signal to the repeater using the UHF antenna at ESA’s Redu Centre in Belgium, then picking up the reply from our L-band antenna.”
Redu’s antenna is 20 meters in diameter, so the shape of the relayed signal was captured in great detail, out of all proportion to surrounding noise.
“We can precisely measure its power, the time the relay took and so on,” added Igor.
More detailed system testing will follow, to completely prove this new type of SAR payload in orbit.
Cospas–Sarsat system.
The international system has been in use for more than three decades, saving some 31,000 lives. Cospas is a Russian acronym for “Space System for the Search of Vessels in Distress,” with Cospas standing for “Search and Rescue Satellite-Aided Tracking.” Ground stations — known as Local User Terminals — pinpoint the source of distress calls using signals relayed by participating satellites, then alert local authorities.
The GPS satellites will also provide a medium-Earth-orbit Sarsat capability and testing is underway. All nine Block IIR satellites carry experimental payloads and all IIF satellites are scheduled to. See “The Distress Alerting Satellite System” for more details.
Swiss-based u‑blox, a provider of GPS/GNSS and wireless semiconductors, has achieved successful satellite positioning using China’s BeiDou Navigation Satellite System. According to u-blox, the technical achievement establishes u-blox as the first GNSS component vendor to demonstrate compatibility with all globally deployed positioning systems: GPS, GLONASS, Galileo, QZSS and now BeiDou.
However, NovAtel has also announced support for the BeiDou Navigation Satellite System on its OEM6 family and select OEMStar GNSS receivers.
Customer demonstration of the u-blox technology will begin during Q1 2013.
“We are thrilled to have achieved this milestone only three weeks after the BeiDou specification was published,” said Thomas Seiler, u-blox CEO. “China will become the world’s most important single market for devices relying on embedded satellite navigation, and u-blox plans to be a major player in this market.”
BeiDou-2 currently has 15 satellites in orbit, offering navigation and positioning services to users in China and Southeast Asia. It will ultimately consist of 35 satellites providing worldwide positioning capability over its open service to within 10 meters accuracy.
u-blox will be demonstrating BeiDou compatibility with their latest GNSS platform at embeddedworld 2013 February 26-28 in Nuremberg, Germany, stand 4A-325.
NovAtel announces support for the BeiDou Navigation Satellite System on its OEM6 family and select OEMStar GNSS receivers.
The long-anticipated BeiDou Navigation Satellite System (BDS) Interface Control Document (ICD) release is a significant milestone that facilitates global acceptance of BeiDou into the growing range of satellite-based positioning applications, NovAtel said.
NovAtel has a long-standing partnership with several Chinese GNSS system manufacturers. This partnership has allowed NovAtel to verify B1 and B2 signal tracking on its latest generation receivers. The company has been supplying GNSS receivers that include the BeiDou constellation since Q4 2010.
“We are excited to see what performance improvements BeiDou will provide to our AdVance RTK, GL1DE and SPAN GNSS/INS positioning algorithms,” said Pat Fenton, NovAtel CTO.
BeiDou positioning has been available through NovAtel’s Chinese partners utilizing the receiver Application Programming Interface (API) feature. With the BeiDou ICD made available to the public, NovAtel is now able to offer BeiDou positioning on its receiver products directly.
Firmware updates for the OEM6 and OEMStar receivers will enable tracking of the BeiDou signal in conjunction with GPS, GLONASS, Galileo and QZSS signals that are currently supported. Over the coming months NovAtel will be working with early-adopter customers to optimize their receiver positioning engines to support the BeiDou signals.
Customers interested in trialing BeiDou functionality on their receivers should contact NovAtel Customer Support at [email protected].
Spirent started shipping BeiDou-ready test systems to customers in 2012. The solution will now be upgraded to full-BeiDou capability using the information from the recently released first full issue of the BeiDou-2 Signal-In-Space Interface Control Document (ICD).
“Spirent has successfully demonstrated BeiDou-2 in simulation systems at its offices in Beijing, China,” said Stuart Smith, product manager for Spirent’s positioning and navigation group. “Prior to the ICD release we used recorded navigation data to enable our systems to drive a full BeiDou receiver and qualify the implementation. With the release of ICD information, navigation data is generated automatically, as with the other constellations that the system simulates.”
Spirent’s BeiDou-2 system includes testing for GPS, GLONASS and Galileo, as well as IRNSS, QZSS and SBAS along with options such as interference generation, MEMS sensor simulation and systems targeted at transport segments.
Background on BeiDou. The BeiDou navigation system, sometimes known as Compass, is a project by China that is being deployed in three phases. BeiDou-2 (the second phase) supports regional operation from a network of geostationary, medium earth orbit and inclined orbit satellites. BeiDou-2 adds to the benefits from “Multi-GNSS” where increased accuracy, availability and integrity are possible from using separate, but interoperable GNSS systems.
As with any other GNSS, systems using BeiDou require testing. As well as testing the BeiDou stand-alone operation, Spirent’s systems enable testing of interoperability and co-existence testing with other navigation systems and sensors.
Septentrio announced on January 7 that it has successfully implemented BeiDou support in the company’s high-precision receiver software, taking advantage of the recent official release of BeiDou’s Interface Control Document (ICD) to including the Chinese satellite navigation signals into its position-velocity-time (PVT) solution.
According to the Belgian GNSS receiver manufacturer, its engineers “are currently processing further data sets to finalize the implementation of full BeiDou support. Although the BeiDou constellation is still being deployed, the data analysis already shows promising results.”
The top panel of Figure 1 compares the height from a stand-alone solution of GPS-only with a GPS+GLONASS solution and a third (in light blue) including BeiDou. “The value added by BeiDou is more than what was expected from a constellation that is still being deployed,” according to Septentrio business development manager Laurent Le Thuaut. “Although the solution is not aided by differential corrections, the position shows an increase in accuracy when sufficient BeiDou satellites are included.”
The bottom panel of Figure 1 shows that, even with the current BeiDou constellation (15 satellites total, of which five are geostationary over China, five in full mid-Earth orbit similar to GPS and GLONASS, and five in inclined geosynchronous orbit over Asia), the total number of satellites used over the European region reached 26 for a short moment.
Figure 2 shows the L1 pseudorange residuals for all constellations individually. This comparison highlights the advantage of the GPS constellation, which builds on two decades of real-time orbit prediction. The BeiDou orbits are “quite accurate for a relatively young constellation, but show typical meter-level jumps when ephemerides are updated,” according to Septentrio.
Septentrio says that the new feature will soon become available on selected company platforms. Users of its multi-constellation receivers will then benefit from improvements in urban availability and signal integrity, thanks to the augmented signal coverage.
On December 29, two days after the Compass Interface Control Document (ICD) was made publicly available, JAVAD GNSS announced that it had tracked “B3 signal from all launched Compass satellites, using TRE-G3T-E E6-band capable receiver. Graphs shows SNR and ‘code-minus-phase’ combination of GEO svn #5 (sat #215 on graph), IGSO svn #8 (sat #218) and MEO svn #14 (sat #224). ‘C/A’ stands for B1, ‘L5’ for B2, ‘CL2’ for B3.”
