The reception of indirect signals, either in the form of non-line-of-sight (NLOS) reception or multipath interference, is a major cause of GNSS position errors in urban environments. We explore the potential of using dual-polarisation antenna technology for detecting and mitigating the reception of NLOS signals and severe multipath interference. The new technique computes the value of the carrier-power-to-noise-density (C/N 0) measurements from left-hand circular polarised outputs subtracted from the right-hand circular polarised C/N 0 counterpart. If this quality is negative, NLOS signal reception is assumed. If the C/N 0 difference is positive, but falls below a threshold based on its lower bound in an open-sky environment, severe multipath interference is assumed. Results from two experiments are presented. Open-field testing was first performed to characterise the antenna behaviour and determine a suitable multipath detection threshold. The techniques were then tested in a dense urban area. Using the new method, two signals in the urban data were identified as NLOS-only reception during the occupation period at one station, while the majority of the remaining signals present were subject to a mixture of NLOS reception and severe multipath interference. The point positioning results were dramatically improved by excluding the detected NLOS measurements. The new technique is suited to a wide range of static ground applications based on our results.

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NLOS GPS signal detection using a dual-polarisation antenna

There are many methods for mitigating GNSS multipath errors. However, none of them completely eliminate the effects of multipath or suit all GNSS applications. A new class of multipath mitigation methods exploit new dual-polarization antenna technology. GNSS signals received direct from the satellites have right-handed circular polarization (RHCP), whereas (singly) reflected signals have left-handed circular polarization (LHCP) or an elliptical polarization that may be expressed as the sum of RHCP and LHCP components. Conventional GNSS user antennas are more sensitive to signals with RHCP, attenuating LHCP signals and reducing, but not eliminating, the multipath errors in the receiver. An antenna with the opposite polarization sensitivity will attenuate the direct signals more than the reflected signals. This can be used to characterizing the reflected signals and thus mitigate the effects of multipath interference.Experimental work using an Antcom dual-polarization antenna and dual geodetic receivers is presented. This verifies that carrier power to noise density, C/N-0, measurements obtained by separately correlating the RHCP and LHCP antenna outputs can be used to distinguish between a low-multipath and moderate-multipath environment. This may be used as the basis of a multipath detection technique.Three different multipath mitigation techniques that use a dual-polarization antenna are proposed. Measurement weighting estimates the code and carrier multipath error standard deviation from the RHCP-LHCP C/N-0 difference and elevation angle. This is used by the navigation processor to discard and reweight measurements. Range-domain multipath correction, uses the pseudo-range, carrier-phase and C/N-0 differences between the outputs of RHCP and LHCP receiver tracking channels, together with antenna calibration data, to estimate corrections to the code and carrier measurements. In tracking-domain multipath mitigation, the RHCP and LHCP correlator outputs are input to common acquisition and tracking algorithms which attempt to separate the direct line of sight and reflected signalsThe design of a novel dual-input GNSS front end, based on direct RF sampling, is presented This will be used, in conjunction with a software GNSS receiver, for future development and testing of multipath mitigation using a dual-polarization antenna.

Novel multipath mitigation methods using a dual-polarization antenna

Modeling and mitigating carrier-phase multipath errors continue to be a significant challenge for high-accuracy positioning using global navigation satellite systems. The multipath error is dependent on the operational environment and therefore cannot be mitigated by differencing techniques. The effect of multipath is accentuated when observables based on linear combinations of measurements from two or more frequencies are formulated. We develop a new carrier-phase multipath error observable that isolates the inter-frequency carrier-phase multipath error for linear combinations of observables, such as wide-lane (WL). Real-time kinematic positioning results from varying baseline lengths show that a significant reduction in between 14 and 47 % in the time to initial ambiguity resolution are achieved by correcting the WL observable using the new carrier-phase multipath error observable.

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The carrier-multipath observable: a new carrier-phase multipath mitigation technique

It is well known that multipath effect remains a dominant error source that affects the positioning accuracy of Global Navigation Satellite System (GNSS) receivers. Significant efforts have been made by researchers and receiver manufacturers to mitigate multipath error in the past decades. Recently, a multipath mitigation technique using dual-polarization antennas has become a research hotspot for it provides another degree of freedom to distinguish the line-of-sight (LOS) signal from the LOS and multipath composite signal without extensively increasing the complexity of the receiver. Numbers of multipath mitigation techniques using dual-polarization antennas have been proposed and all of them report performance improvement over the single-polarization methods. However, due to the unpredictability of multipath, multipath mitigation techniques based on dual-polarization are not always effective while few studies discuss the condition under which the multipath mitigation using a dual-polarization antenna can outperform that using a single-polarization antenna, which is a fundamental question for dual-polarization multipath mitigation (DPMM) and the design of multipath mitigation algorithms. In this paper we analyze the characteristics of the signal received by a dual-polarization antenna and use the maximum likelihood estimation (MLE) to assess the theoretical performance of DPMM in different received signal cases. Based on the assessment we answer this fundamental question and find the dual-polarization antenna’s capability in mitigating short delay multipath—the most challenging one among all types of multipath for the majority of the multipath mitigation techniques. Considering these effective conditions, we propose a dual-polarization sequential iterative maximum likelihood estimation (DP-SIMLE) algorithm for DPMM. The simulation results verify our theory and show superior performance of the proposed DP-SIMLE algorithm over the traditional one using only an RHCP antenna.

Mitigating Multipath Bias Using a Dual-Polarization Antenna: Theoretical Performance, Algorithm Design, and Simulation.

In urban canyons, transportation systems localization based on GNSS (Global Navigation Satellite System) can be strongly affected, due to NLOS and Multipath effects. The GNSS signal can be reflected by the obstacles near of the vehicle (buildings, buses, Trees...), and these reflections degrade significantly the positioning accuracy.To improve positioning performance of intelligent transportation systems in harsh environments, several solutions in the literature have shown that a good signal classification can significantly improve positioning accuracy in signal degradation environments but is limited by low reliability.In this research work, we address a very challenging problem related to GNSS signals reception state detection, classified as a Decision problem.A new GNSS signal classifier system based on the fusion of information provided by RHCP and LHCP antennas, and a machine learning technique is proposed.The novelty of our proposed classifier summarizes in exploiting the characteristics and potential of the RHCP and LHCP antennas to process the GNSS signal (a new GNSS receiver is proposed). Furthermore, using together a machine learning technique, namely, Decision Trees algorithm, and data fusion is a promising approach for improving data analysis and classification, especially in complex scenarios.The proposed DecisionTrees-based classifier has used the satellite elevation and C/N0-R-L ratio, which is the difference between the left-hand circular polarized (LHCP) C/N0 (Carrier-to-noise) and the right-hand circular polarized (RHCP) C/N0.Effective and proper data classification by applying the proposed classifier is demonstrated through several field tests in urban areas, Calais, France. We obtain an accuracy of 99% over KNN and SVM classification techniques.

A Robust GNSS LOS/Multipath Signal Classifier based on the Fusion of Information and Machine Learning for Intelligent Transportation Systems

This paper presents a GPS multipath mitigation method using a dual circularly polarized antenna array and a multi-channel receiver. The method is based on the exploitation of both polarization and spatial diversity associated with a GPS signal and its multipath signals available at the receiver input. Conventional GPS antennas are right-hand circularly polarized (RHCP) to suppress multipath contributions to the input. This polarization-based discrimination of multipath signal cannot completely eliminate multipath induced GPS range measurement errors. We present an algorithm that performs spatial processing on the input from the left-hand circular polarized (LHCP) array with an increased relative strength of the multipath signal, thereby providing improved multipath angle of arrival (AOA) estimation. With the known multipath AOA and direct signal AOA (which can be obtained from almanac/ephemeris together with the antenna attitude or estimated in a separate process), we can then take advantage of the spatial diversity of the direct signal and multipath by applying null-steering to the RHCP array input. The paper presents the algorithm and simulation results for a uniform linear array receiving one direct signal and one multipath. Our preliminary studies showed that the multipath AOA estimator produces negligible error if the direct signal and multipath AOA are not close to each other (more than 5 degrees apart) and that the direct signal is not at low elevation. The results also suggested that longer time delay between the direct and multipath signal will increase multipath AOA estimation error but this increase is tolerable. Furthermore, we demonstrated that the multipath estimation improves with increasing spatial diversity for multipath and direct GPS signals even if the signal arrivals are close in time. Finally, we demonstrated that the multipath mitigation technique does produce an improved receiver correlator function which directly impacts the GPS code range measurement accuracy.

Mitigation of GPS Multipath Using Polarization and Spatial Diversities


 Rapid earthquake magnitude estimation from real-time space-based geodetic observation streams provides an opportunity to mitigate the impact of large and potentially damaging earthquakes by issuing low-latency warnings prior to any significant and destructive shaking. Geodetic contributions to earthquake characterization and rapid magnitude estimation have evolved in the last 20 yr, from post-processed seismic waveforms to, more recently, improved capacity of regional geodetic networks enabled real-time Global Navigation Satellite System seismology using precise point positioning (PPP) displacement estimates. In addition, empirical scaling laws relating earthquake magnitude to peak ground displacement (PGD) at a given hypocentral distance have proven effective in rapid earthquake magnitude estimation, with an emphasis on performance in earthquakes larger than ∼Mw 6.5 in which near-field seismometers generally saturate. Although the primary geodetic contributions to date in earthquake early warning have focused on the use of 3D position estimates and displacements, concurrent efforts in time-differenced carrier phase (TDCP)-derived velocity estimates also have demonstrated that this methodology has utility, including similarly derived empirical scaling relationships. This study builds upon previous efforts in quantifying the ambient noise of three-component ground-displacement and ground-velocity estimates. We relate these noise thresholds to expected signals based on published scaling laws. Finally, we compare the performance of PPP-derived PGD to TDCP-derived peak ground velocity (PGV), given several rich event datasets. Our results indicate that TDCP-PGV is more likely than PPP-PGD to detect intermediate magnitude (∼Mw 5.0–6.0) earthquakes, albeit with greater magnitude estimate uncertainty and across smaller epicentral distances. We conclude that the computationally lightweight TDCP-derived PGV magnitude estimation is complementary to PPP-derived PGD magnitude estimates, which could be produced at the network edge at high rates and with increased sensitivity to ground motion than current PPP estimates.

Comparing Sensitivities of Geodetic Processing Methods for Rapid Earthquake Magnitude Estimation

The next generation of GNSS promises new satellite constellation and signal designs that will improve capabilities and performances for all users. Frequency Hopping Modulation (FHM) is one of the signal designs that is being considered due to its potential robustness against interference and multipath. In this work, we assess the impact of the ionosphere on coherent FHM signals. In particular, we look at the waveform and autocorrelation properties of the FHM signal before and after passing through the refractive ionosphere channel. Then we highlight the ambiguity between code phase and ionosphere total electron content (TEC) effects on the received signal, and we discuss acquisition performance of such signal parameters for two coherent FHM signal designs: 1) using a 2-ary hopping sequence between 1227.6 and 1575.42 MHz, and 2) using a 19-ary hopping sequence of evenly-spaced frequencies between 1227.6 and 1267.6 MHz. 

Frequency-Hopping Modulation Signals for GNSS

This study investigates the meteorological and ionospheric responses of a meteorological tsunamis (meteotsunamis) event that impacted southwest Kyushu, Japan on 25 February 2009. This event is identified by local sea-level pressure anomalies started at ~11:27 UT and lasted 18 hours with a maximum air pressure disturbance of ~1.5 hpa. Sea surface height anomalies were observed at ~13:00 UT and lasted for about 26 hours with a maximum perturbation of ~290 cm. Such perturbations of both sea level and sealevel pressure are likely associated with two subsequent traveling ionospheric disturbances (TIDs) events which were observed in total electron content (TEC) derived from ground-based Global Navigation Satellite System (GNSS) networks in Japan. The first TIDs occurred at ~11:41 UT which is 1.5 hr before the meteotsunami could be an early warning of meteotsunami. It has a wave front aligned in the northwest-southeast direction and propagated in the direction of southwest. This TIDs is more likely a manifestation of gravity waves (GWs) which might accelerate the growth rate of Perkins-type nighttime medium-scale TIDs (MSTIDs). The second TIDs took place at ~21:42 UT. Its wave front is characterized by concentric rings (referred to as CTIDs), likely corresponding to concentric GWs (CGWs). The characteristics of the CTIDs are corroborated with radar echo intensity measurements obtained from the Automated Meteorological Data Acquisition System (AMeDAS) and with the optimal waves source searching technique. Based on the radar echo intensity and optimal waves source searching results, the generation mechanism of the CTIDs could be meteotsunami and/ or deep convection. This suggests further investigation of ionospheric responses due to meteotsunami is needed. 

Jade Morton

Papers

Mitigation of GPS Multipath Using Polarization and Spatial Diversities

Comparing Sensitivities of Geodetic Processing Methods for Rapid Earthquake Magnitude Estimation

Frequency-Hopping Modulation Signals for GNSS

Identification of Meteotsunami through GNSS Traveling Ionospheric Disturbance Observations

Mitigation of Global Navigation Satellite System Cycle Slips Due to Scintillation Using Radio Backpropagation