Initial L2C Multipath and Noise Performance Analysis from Real Data (original) (raw)
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Journal MultipathMitigation Final v02 RadioEngineering 31Aug12
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 twopath 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/N 0 -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.
Multipath and Ionosphere Analysis for Satellite Navigation Applications
The measurements performed by a GPS receiver are subject to a various errors related to the signal propagation. Some of these errors affect code and carrier measurements or L1 and L2 measurements in a different way: Using proper linear combinations of dual-frequency receiver measurements, multipath effects and ionospheric delays can be isolated and studied.
Advanced Multipath Mitigation Techniques for Satellite-Based Positioning Applications
Multipath remains a dominant source of ranging errors in Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS) or the future European satellite navigation system Galileo. Multipath is generally considered undesirable in the context of GNSS, since the reception of multipath can make significant distortion to the shape of the correlation function used for time delay estimation. However, some wireless communications techniques exploit multipath in order to provide signal diversity though in GNSS, the major challenge is to effectively mitigate the multipath, since we are interested only in the satellitereceiver transit time offset of the Line-Of-Sight (LOS) signal for the receiver's position estimate. Therefore, the multipath problem has been approached from several directions in order to mitigate the impact of multipath on navigation receivers, including the development of novel signal processing techniques. In this paper, we propose a maximum likelihood-based technique, namely, the Reduced Search Space Maximum Likelihood (RSSML) delay estimator, which is capable of mitigating the multipath effects reasonably well at the expense of increased complexity. The proposed RSSML attempts to compensate the multipath error contribution by performing a nonlinear curve fit on the input correlation function, which finds a perfect match from a set of ideal reference correlation functions with certain amplitude(s), phase(s), and delay(s) of the multipath signal. It also incorporates a threshold-based peak detection method, which eventually reduces the code-delay search space significantly. However, the downfall of RSSML is the memory requirement which it uses to store the reference correlation functions. The multipath performance of other delay-tracking methods previously studied for Binary Phase Shift Keying-(BPSK-) and Sine Binary Offset Carrier-(SinBOC-) modulated signals is also analyzed in closed loop model with the new Composite BOC (CBOC) modulation chosen for Galileo E1 signal. The simulation results show that the RSSML achieves the best multipath mitigation performance in a uniformly distributed two-to-four paths Rayleigh fading channel model for all three modulated signals.
A Slope-Based Multipath Estimation technique for mitigating short-delay multipath in GNSS receivers
The everlasting public interest on location and positioning services has originated a demand for a high performance Global Navigation Satellite System (GNSS), such as the Global Positioning System or the future European satellite navigation system, Galileo. The performance of GNSS is subject to several errors, such as ionosphere delay, troposphere delay, receiver noise and multipath. Among all these errors, multipath is the main limiting factor in precision-oriented GNSS applications. The reception of multipath creates a bias into the time delay estimate of the delay lock loop of a conventional navigation receiver, which eventually leads to an error in the receiver's position estimate. In order to mitigate the multipath influence on navigation receivers, the multipath problem has been approached from several directions, including the development of novel signal processing techniques. Many of these techniques rely on modifying the tracking loop discriminator in order to make it resistant to multipath. These techniques have proved very efficient against multipath having a medium or large delay with respect to the Line-Of-Sight (LOS) signal. In general, the multipath errors are largely reduced for multipath delays greater than around 0.1 chips (which is about 2 9 . 3 m e t e r s f o r G a l i l e o E 1 O p e n S e r v i c e ( O S ) s i g n a l ) . Theoretically, this constitutes a remarkable improvement as compared to simpler techniques such as narrow Early-Minus-Late (nEML) tracking loop. However, in practice, most of the multipath signals enter the receiver with short-delay with respect to LOS signal, making most of these mitigation techniques partially ineffective. In this paper, we propose a new multipath estimation technique, namely the Slope-Based Multipath Estimation (SBME), which is capable of mitigating the short-delay multipath (i.e., multipath delays less than 0.35 chips) quite well compared with other state-of-the-art mitigation techniques, such as the nEML and the High Resolution Correlators (HRC). The proposed SBME first derives a multipath estimation equation by utilizing the correlation shape of the ideal normalized correlation function of a Binary Phase Shift Keying (BPSK)-or Multiplexed Binary Offset Carrier (MBOC)-modulated signal, which is then used to compensate for the multipath bias of a nEML tracking loop. It is worth to mention here that the SBME requires an additional correlator at the late side of the correlation function, and it is used inconjunction with a nEML tracking loop. The multipath performance of the above-mentioned mitigation techniques is presented for Galileo E1 OS and GPS L1 C/A signals from theoretical as well as simulation perspective.
2009
This paper focuses on the analysis of GPS L1 signals when propagating indoors. Two criteria are proposed with the aim of detecting the presence of multipath, which is one of the major degradations experienced by GPS receivers when operating in indoor environments. The proposed criteria have been evaluated through an exhaustive field test by using a High Sensitivity GNSS software receiver. The results confirm the validity of these criteria and allow a better understanding of the underlying propagation phenomena of GPS signals.
Multifunctional Operation and Application of GPS
Multipath is the major concern in GPS receivers that fade the actual GPS signal causes positioning error up to 10 m so special care need to be taken to mitigate the multipath effects. Numerous methods like hardware based antenna arrays technique, receiver based narrow correlator receiver, double-delta discriminator, Adaptive Multipath Estimator, Wavelet Transformation and Particle filter, Kalman filter based post receiver methods etc. used to resolve the problem. But some of the methods can only reduce code multipath error but not effective in eliminating carrier multipath error. Most of these techniques are based on the assumption that the Line-of-Sight (LOS) signal is stronger than the Non-Line of-Sight (NLOS) signals. However, in the scenarios where the LOS signal is weaker than the composite multipath signal, this approach may result in a bias in code tracking. In this chapter, different types of multipath mitigation and its limitation are described. The recent development in sparse signal processing based blind channel estimation is investigated to compensate the multipath error. The Rayleigh and Rician fading model with different multipath parameters are simulated to test the urban scenario. The inverse problem of finding the GPS signal is addressed based on the deconvolution approach. To solve linear inverse problems, the suitable kind of appropriate objective function has been formulated to find the signal of interest. By exploiting this methods, the signal is observed and the carrier and code tracking loop parameters are computed with minimal error.
Analysis of Multipath Mitigation Techniques for Satellite-based Positioning Applications
2011
Multipath remains a dominant source of ranging errors in any Global Navigation Satellite System (GNSS), such as the Global Positioning System (GPS) or the developing European satellite navigation system Galileo. Multipath is undesirable in the context of GNSS, since the reception of multipath can create significant distortion to the shape of the correlation function used in the time delay estimate of a Delay Locked Loop (DLL) of a navigation receiver, leading to an error in the receiver's position estimate. Therefore, in order to mitigate the impact of multipath on a navigation receiver, the multipath problem has been approached from several directions, including the development of novel signal processing techniques. Many of these techniques rely on modifying the tracking loop discriminator (i.e., the DLL and its enhanced variants) in order to make it resistant to multipath, but their performance in severe multipath scenarios is still rather limited. In this thesis, the Author particularly addresses the challenge of overcoming the difficulties due to multipath propagation by developing several novel correlation-based multipath mitigation techniques, ranging from simple DLL based approach to advanced multi-correlator based solution, whichever is appropriate according to the requirements of positioning applications (i.e., low-cost simpler implementation versus better accuracy). The proposed novel multipath mitigation techniques can be categorized into three major categories considering their implementation complexity: i. the advanced technique, which requires many correlators and have relatively complex implementation; ii. the simple technique, which requires only a few correlators; and iii. the combined technique, which is a combination of two other techniques and has moderate complexity.
Simulation and Performance Evaluations of the New GPS L5 and L1 Signals
Wireless Communications and Mobile Computing, 2017
The Global Positioning System (GPS) signals are used for navigation and positioning purposes by a diverse set of users. As a part of GPS modernization effort L5 has been recently introduced for better accuracy and availability service. This paper intends to study and simulate the GPS L1/L5 signal in order to fulfill the following two objectives. The first aim is to point out some important features/differences between current L1 (whose characteristics have been fairly known and documented) and new L5 GPS signal for performance evaluation purpose. The second aim is to facilitate receiver development, which will be designed and assembled later for the actual acquisition of GPS data. Simulation has been carried out for evaluation of correlation properties and link budgeting for both L1 and L5 signals. The necessary programming is performed in Matlab.