A particle filtering approach for joint detection/estimation of multipath effects on GPS measurements

Multipath propagation causes major impairments to Global Positioning System (GPS) based navigation. Multipath results in biased GPS measurements, hence inaccurate position estimates. In this work, multipath effects are considered as abrupt changes affecting the navigation system. A multiple model formulation is proposed whereby the changes are represented by a discrete valued process. The detection of the errors induced by multipath is handled by a Rao-Blackwellized particle filter (RBPF). The RBPF estimates the indicator process jointly with the navigation states and multipath biases. The interest of this approach is its ability to integrate a priori constraints about the propagation environment. The detection is improved by using information from near future GPS measurements at the particle filter (PF) sampling step. A computationally modest delayed sampling is developed, which is based on a minimal duration assumption for multipath effects. Finally, the standard PF resampling stage is modified to include an hypothesis test based decision step

Multipath Estimation in Urban Environments from Joint GNSS Receivers and LiDAR Sensors

In this paper, multipath error on Global Navigation Satellite System (GNSS) signals in urban environments is characterized with the help of Light Detection and Ranging (LiDAR) measurements. For this purpose, LiDAR equipment and Global Positioning System (GPS) receiver implementing a multipath estimating architecture were used to collect data in an urban environment. This paper demonstrates how GPS and LiDAR measurements can be jointly used to model the environment and obtain robust receivers. Multipath amplitude and delay are estimated by means of LiDAR feature extraction and multipath mitigation architecture. The results show the feasibility of integrating the information provided by LiDAR sensors and GNSS receivers for multipath mitigatio

GPS Multipath Detection in the Frequency Domain

Multipath is among the major sources of errors in precise positioning using GPS and continues to be extensively studied. Two Fast Fourier Transform (FFT)-based detectors are presented in this paper as GPS multipath detection techniques. The detectors are formulated as binary hypothesis tests under the assumption that the multipath exists for a sufficient time frame that allows its detection based on the quadrature arm of the coherent Early-minus-Late discriminator (Q EmL) for a scalar tracking loop (STL) or on the quadrature (Q EmL) and/or in-phase arm (I EmL) for a vector tracking loop (VTL), using an observation window of N samples. Performance analysis of the suggested detectors is done on multipath signal data acquired from the multipath environment simulator developed by the German Aerospace Centre (DLR) as well as on multipath data from real GPS signals. Application of the detection tests to correlator outputs of scalar and vector tracking loops shows that they may be used to exclude multipath contaminated satellites from the navigation solution. These detection techniques can be extended to other Global Navigation Satellite Systems (GNSS) such as GLONASS, Galileo and Beidou.Comment: 2016 European Navigation Conference (ENC 2016), May 2016, Helsinki, Finland. Proceedings of the 2016 European Navigation Conference (ENC 2016

A GPS Code Tracking Receiver Design for Multipath Mitigation Using Maximum Likelihood Estimation

The NAVSTAR Global Positioning System (GPS) is currently used in many applications requiring precise positioning data. Improving the precise positioning information requires the removal of errors that perturb the received signals. The errors introduced by multiple propagation channels, termed multipath, are not easily removed. These channels are caused by reflective surfaces near the receiver. As such, multipath is uncorrelated between receivers and, thus, cannot be removed through differencing techniques. This thesis investigates a GPS code tracking loop design which uses maximum likelihood (ML) estimation to determine amplitude and phase information of the multipath signal which are used to adjust code tracking to account for multipath effects. Analysis of the operations that govern this design for the case of a single reflection shows that it has no steady state tracking error. Results of simulations indicate that the code tracking loop, in conjunction with the MLE, mitigate the effects of multipath and improves code tracking performance over the narrow correlator NCDLL for most scenarios analyzed. Overall results of simulations indicate that the implementation of the maximum likelihood estimator (MLE) in conjunction with the code tracking loop has the potential to enhance code tracking performance over that offered by the narrow correlator NCDLL in a GPS environment

Receiver-channel based adaptive blind equalization approach for GPS dynamic multipath mitigation

AbstractAiming at mitigating multipath effect in dynamic global positioning system (GPS) satellite navigation applications, an approach based on channel blind equalization and real-time recursive least square (RLS) algorithm is proposed, which is an application of the wireless communication channel equalization theory to GPS receiver tracking loops. The blind equalization mechanism builds upon the detection of the correlation distortion due to multipath channels; therefore an increase in the number of correlator channels is required compared with conventional GPS receivers. An adaptive estimator based on the real-time RLS algorithm is designed for dynamic estimation of multipath channel response. Then, the code and carrier phase receiver tracking errors are compensated by removing the estimated multipath components from the correlators’ outputs. To demonstrate the capabilities of the proposed approach, this technique is integrated into a GPS software receiver connected to a navigation satellite signal simulator, thus simulations under controlled dynamic multipath scenarios can be carried out. Simulation results show that in a dynamic and fairly severe multipath environment, the proposed approach achieves simultaneously instantaneous accurate multipath channel estimation and significant multipath tracking errors reduction in both code delay and carrier phase

Effects of Multipath and Oversampling on Navigation Using Orthogonal Frequency Division Multiplexed Signals of Opportunity

The Global Positioning System (GPS) has become the primary system for navigation and precise positioning. GPS has limitations, though, and is not suitable in environments where a line-of-site (LOS) path to multiple satellites is not available. Reliable alternatives need to be developed to provide GPS-like positioning when GPS is unavailable. One such alternative is to use signals of opportunity (SoOP). This concept refers to navigation using signals which inherently exist in the environment and were developed for non-navigation applications. This research focuses on exploiting the Orthogonal Frequency Division Multiplexed (OFDM) signal for the purpose of navigation. An algorithm was developed to simulate a transmitter, receiver, channel noise, and multipath propagation. A transmitter and reference receiver, both at known locations, and a mobile receiver at an unknown location were used to conduct simulations with a transmitted OFDM signal in a Rayleigh-distributed multipath environment. The OFDM signal structure was exploited by using its cyclic prefix in a correlation process to find the first symbol boundary in each received signal. Each receiver calculates statistical features about each symbol in the received signal. These two sets of data are then correlated in order find the difference in symbol arrival times. The simulations were run for varying levels of oversampling in an effort to gain more accurate results by decreasing the sample period. Results show that oversampling the signal only slightly reduces errors in the symbol boundary correlation process, while multipath has a significant impact on correlation performance. It was also found that increasing the window size significantly improved feature correlator performance and yielded promising results even in the presence of high multipath environments

Effectiveness of observation-domain sidereal filtering for GPS precise point positioning

Sidereal filtering is a technique used to reduce errors caused by multipath in the positioning of static receivers via the Global Positioning System (GPS). It relies upon the receiver and its surrounding environment remaining static from one day to the next and takes advantage of the approximately sidereal repeat time of the GPS constellation geometry. The repeating multipath error can thus be identified, usually in the position domain, and largely removed from the following day. We describe an observation-domain sidereal filter algorithm that operates on undifferenced ionospheric-free GPS carrier phase measurements to reduce errors caused by multipath. It is applied in the context of high-rate (1 Hz) precise point positioning of a static receiver. An observation-domain sidereal filter (ODSF) is able to account for the slightly different repeat times of each GPS satellite, unlike a position-domain sidereal filter (PDSF), and can hence be more effective at reducing high-frequency multipath error. Using 8-h long datasets of GPS measurements from two different receivers with different antenna types and contrasting environments, the ODSF algorithm is shown overall to yield a position time series 5–10 % more stable, in terms of Allan deviation, than a PDSF over nearly all time intervals below about 200 s in length. This may be particularly useful for earthquake and tsunami early warning systems where the accurate measurement of small displacements of the ground over the period of just a few minutes is crucial. However, the sidereal filters are also applied to a third dataset during which two short episodes of particularly high-frequency multipath error were identified. These two periods are analyzed in detail and illustrate the limitations of using sidereal filters with important implications for other methods of correcting for multipath at the observation level

Wavelet packets based denoising method for measurement domain repeat-time multipath filtering in GPS static high-precision positioning

Repeatable satellite orbits can be used for multipath mitigation in GPS-based deformation monitoring and other high-precision GPS applications that involve continuous observation with static antennas. Multipath signals at a static station repeat when the GPS constellation repeats given the same site environment. Repeat-time multipath filtering techniques need noise reduction methods to remove the white noise in carrier phase measurement residuals in order to retrieve the carrier phase multipath corrections for the next day. We propose a generic and robust three-level wavelet packets based denoising method for repeat-time-based carrier phase multipath filtering in relative positioning; the method does not need tuning to work with different data sets. The proposed denoising method is tested rigorously and compared with two other denoising methods. Three rooftop data sets collected at the University of Nottingham Ningbo China and two data sets collected at three Southern California Integrated GPS Network high-rate stations are used in the performance assessment. Test results of the wavelet packets denoising method are compared with the results of the resistor–capacitor (RC) low-pass filter and the single-level discrete wavelet transform (DWT) denoising method. Multipath mitigation efficiency in carrier phase measurement domain is shown by spectrum analysis of two selected satellites in two data sets. The positioning performance of the repeat-time-based multipath filtering techniques is assessed. The results show that the performance of the three noise reduction techniques is about 1–46 % improvement on positioning accuracy when compared with no multipath filtering. The statistical results show that the wavelet packets based denoising method is always better than the RC filter by 2–4 %, and better than the DWT method by 6–15 %. These results suggest that the proposed wavelet packets based denoising method is better than both the DWT method and the relatively simple RC low-pass filter for noise reduction in multipath filtering. However, the wavelet packets based denoising method is not significantly better than the RC filter

Analysis and Simulation of a New Code Tracking Loop for GPS Multipath Mitigation

This thesis proposes a new direct sequence spread spectrum (DS/SS) code phase tracking loop which mitigates the effects of multipath interference on code phase tracking error; such errors can translate to significant range measurement errors in DS/SS ranging systems such as Global Positioning System (GPS). The new code tracking loop, called the modified RAKE delay lock loop (MRDLL), uses maximum likelihood (ML) signal parameter estimation to determine the amplitude, carrier phase, and relative propagation delay of both a direct path and a reflected signal; a multiple correlator code phase tracking loop then exploits these ML signal estimates to remove the tracking error introduced by the reflection. A preliminary analysis showed that the MRDLL\u27s linear tracking region varied with the reflected signal parameters; therefore, an adaptive loop controller (ALC) was introduced to allow the loop designer to fix dynamic specifications such as loop natural frequency. Analysis and computer simulations demonstrated that, when multipath was present, the MRDLL exhibited a significantly lower steady-state code phase tracking error than that of the standard noncoherent delay lock loop (NCDLL), which is typically used in GPS receivers. In an ideal multipath-free environment, the NCDLL is still the best choice for code phase tracking. This GPS receiver design technology will benefit the entire aviation community by eliminating or reducing the dominant source of error in differential GPS-based instrument landing systems, resulting in improved ILS safety, reliability, and integrity. In relative GPS applications, such as precision guided munitions, lethality is improved via elimination of multipath contribution to targeting error. In all GPS applications, the (no longer dominant) error contribution of multipath can be eliminated, yielding enhanced positioning accuracy

Analysis of Multipath Mitigation Techniques with Land Mobile Satellite Channel Model

Multipath is undesirable for Global Navigation Satellite System (GNSS) receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS) path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Multipath is undesirable for Global Navigation Satellite System (GNSS) receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS) path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Mobile Satellite (LMS) channel model [1]-[4], developed at the German Aerospace Center (DLR). The DLR LMS channel model is widely used for simulating the positioning accuracy of mobile satellite navigation receivers in urban outdoor scenarios. The main objective of this paper is to present a comprehensive analysis of some of the most promising techniques with the DLR LMS channel model in varying multipath scenarios. Four multipath mitigation techniques are chosen herein for performance comparison, namely, the narrow Early-Minus-Late (nEML), the High Resolution Correlator, the C/N0-based two stage delay tracking technique, and the Reduced Search Space Maximum Likelihood (RSSML) delay estimator. The first two techniques are the most popular and traditional ones used in nowadays GNSS receivers, whereas the later two techniques are comparatively new and are advanced techniques, recently proposed by the authors. In addition, the implementation of the RSSML is optimized here for a narrow-bandwidth receiver configuration in the sense that it now requires a significantly less number of correlators and memory than its original implementation. The simulation results show that the reduced-complexity RSSML achieves the best multipath mitigation performance in moderate-to-good carrier-to-noise density ratio with the DLR LMS channel model in varying multipath scenarios