Advanced Multipath Mitigation Techniques for Satellite-Based Positioning Applications. (25th October 2010)

• Record Type: Journal Article
• Authors: Bhuiyan, Mohammad Zahidul H.; Lohan, Elena Simona
• Other Names: Julien Olivier Academic Editor.
• Is Part Of: International journal of navigation and observation. Volume 2010(2010)
• Publication Date: 2010-10-25
• Subjects: Navigation -- Periodicals; Remote sensing -- Periodicals; Geographic information systems -- Periodicals; Global Positioning System -- Periodicals; Earth sciences -- Periodicals; Environmental monitoring -- Periodicals; Navigation; Télédétection; Systèmes d'information géographique; GPS; Sciences de la terre; Environnement -- Surveillance; Earth sciences; Environmental monitoring; Geographic information systems; Global Positioning System; Navigation; Remote sensing; Periodicals; Electronic journals; 629.045
• DOI: 10.1155/2010/412393
• Languages: English
• ISSNs: 1687-5990

Abstract

Abstract : 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 satellite-receiver 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.