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

A Graphical Approach to GPS Software-Defined Receiver Implementation

Global positioning system (GPS) software-defined receivers (SDRs) offer many advantages over their hardwarebased counterparts, such as flexibility, modularity, and upgradability. A typical GPS receiver is readily expressible as a block diagram, making a graphical approach a natural choice for implementing GPS SDRs. This paper presents a real-time, graphical implementation of a GPS SDR, consisting of two modes: acquisition and tracking. The acquisition mode performs a twodimensional fast Fourier transform (FFT)-based search over code offsets and Doppler frequencies. The carrier-aided code tracking mode consists of the following main building blocks: correlators, code and carrier phase detectors, code and carrier phase filters, a code generator, and a numerically-controlled oscillator. The presented GPS SDR provides an abstraction level that enables future research endeavors.Aerospace Engineering and Engineering Mechanic

Analysis of Ionospheric Scintillations using Wideband GPS L1 C/A Signal Data

A non-real-time GPS receiver has been developed and tested for use in scintillation analysis. The receiver consists of a digital storage receiver and non-real-time software acquisition and tracking algorithms. The goal of this work is to shed light on the behavior of strongly scintillating signals: signals which cause conventional GPS receivers to lose carrier lock. The receiver collects wideband GPS L1 digital data sampled at 5.7 MHz using an RF front-end and stores it on disk for post-processing. It processes the data off-line to determine carrier signal amplitude and phase variations during scintillations. The main processing algorithms are traditional code delay and carrier frequency acquisition algorithms and special signal processing algorithms that effectively function as a delay-locked loop and phase-locked loop. The tracking algorithms use non-causal smoothing techniques in order to optimally reconstruct the phase and amplitude variations of a scintillating signal. These techniques are robust against the deep power fades and strong phase fluctuations characteristic of scintillating signals. To test the receiver, scintillation data were collected in Cauchoeira Paulista, Brazil, from December 4 to 6, 2003. The data set spans several hours and includes times when one or more satellite signals are scintillating. The smoothing algorithm has been used to determine the carrier amplitude and phase time histories of the scintillating signals along with the distortion of the pseudorandom noise (PRN) code’s autocorrelation function. These quantities provide a characterization of scintillation that can be used to study the physics of scintillations or to provide off-line test cases to evaluate a tracking algorithm’s ability to maintain signal lock during scintillations.Aerospace Engineering and Engineering Mechanic

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

Development and Demonstration of a TDOA-Based GNSS Interference Signal Localization System

Background theory, a reference design, and demonstration results are given for a Global Navigation Satellite System (GNSS) interference localization system comprising a distributed radio-frequency sensor network that simultaneously locates multiple interference sources by measuring their signals’ time difference of arrival (TDOA) between pairs of nodes in the network. The end-to-end solution offered here draws from previous work in single-emitter group delay estimation, very long baseline interferometry, subspace-based estimation, radar, and passive geolocation. Synchronization and automatic localization of sensor nodes is achieved through a tightly-coupled receiver architecture that enables phase-coherent and synchronous sampling of the interference signals and so-called reference signals which carry timing and positioning information. Signal and crosscorrelation models are developed and implemented in a simulator. Multiple-emitter subspace-based TDOA estimation techniques are developed as well as emitter identification and localization algorithms. Simulator performance is compared to the CramérRao lower bound for single-emitter TDOA precision. Results are given for a test exercise in which the system accurately locates emitters broadcasting in the amateur radio band in Austin, TX.Aerospace Engineering and Engineering Mechanic

Benchmarking CPUs and GPUs on embedded platforms for software receiver usage

Smartphones containing multi-core central processing units (CPUs) and powerful many-core graphics processing units (GPUs) bring supercomputing technology into your pocket (or into our embedded devices). This can be exploited to produce power-efficient, customized receivers with flexible correlation schemes and more advanced positioning techniques. For example, promising techniques such as the Direct Position Estimation paradigm or usage of tracking solutions based on particle filtering, seem to be very appealing in challenging environments but are likewise computationally quite demanding. This article sheds some light onto recent embedded processor developments, benchmarks Fast Fourier Transform (FFT) and correlation algorithms on representative embedded platforms and relates the results to the use in GNSS software radios. The use of embedded CPUs for signal tracking seems to be straight forward, but more research is required to fully achieve the nominal peak performance of an embedded GPU for FFT computation. Also the electrical power consumption is measured in certain load levels.Peer ReviewedPostprint (published version

On the Impact of Channel Cross-Correlations in High-Sensitivity Receivers for Galileo E1 OS and GPS L1C Signals

One of the most promising features of the modernized global navigation satellite systems signals is the presence of pilot channels that, being data-transition free, allow for increasing the coherent integration time of the receivers. Generally speaking, the increased integration time allows to better average the thermal noise component, thus improving the postcorrelation SNR of the receiver in the acquisition phase. On the other hand, for a standalone receiver which is not aided or assisted, the acquisition architecture requires that only the pilot channel is processed, at least during the first steps of the procedure. The aim of this paper is to present a detailed investigation on the impact of the code cross-correlation properties in the reception of Galileo E1 Open Service and GPS L1C civil signals. Analytical and simulation results demonstrate that the S-curve of the code synchronization loop can be affected by a bias around the lock point. This effect depends on the code cross-correlation properties and on the receiver setup. Furthermore, in these cases, the sensitivity of the receiver to other error sources might increase, and the paper shows how in presence of an interfering signal the pseudorange bias can be magnified and lead to relevant performance degradatio

Unambiguous Tracking Method Based on Combined Correlation Functions for sine/cosine-BOC CBOC and AltBOC Modulated Signals

Unambiguous tracking for Binary Offset Carrier (BOC) modulated signals is an important requirement of modern Global Navigation Satellite System (GNSS) receivers. An unambiguous tracking method based on combined correlation functions for even/odd order sine/cosine-BOC, Composite BOC(CBOC) and Alternate BOC(AltBOC) modulated signals is proposed. Firstly, a unitary mathematical formulation for all kinds of BOC modulations is introduced. Then an unambiguous tracking method is proposed based on the formulation and the idea of pseudo correlation function (PCF) method. Finally, the tracking loop based on the proposed method is designed. Simulation results indicate that the proposed method can remove side peaks while retaining the sharp main peak for all kinds of BOC modulations. The tracking performance for AltBOC is examined and the results show that the proposed method has better performance in thermal noise and long-delay multipath mitigation than the traditional unambiguous tracking methods

Range filtering for sequential GPS receivers with external sensor augmentation

The filtering of the satellite range and range-rate measurements from single channel sequential Global Positioning System receivers is usually done with an extended Kalman filter which has state variables defined in terms of an orthogonal navigation reference frame. An attractive suboptimal alternative is range-domain filtering, in which the individual satellite measurements are filtered separately before they are combined for the navigation solution. The main advantages of range-domain filtering are decreased processing and storage requirements and simplified tuning. Several range filter mechanization alternatives are presented, along with an innovative approach for combining the filtered range-domain quantities to determine the navigation state estimate. In addition, a method is outlined for incorporating measurements from auxiliary sensors such as altimeters into the navigation state estimation scheme similarly to the satellite measurements. A method is also described for incorporating inertial measurements into the navigation state estimator as a process driver

A rao-blackwellized particle filter for INS/GPS integration

The localization performance of a navigation system can be improved by coupling different types of sensors. This paper focuses on INS-GPS integration. INS and GPS measurements allow to dene a non-linear state space model, which is appropriate to particle ltering. This model being conditionally linear Gaussian, a Rao-Blackwellization procedure can be applied to reduce the variance of the estimates