Multipath remains a dominant source of ranging errors in Global Navigation Satellite Systems (GNSS), such as the Global\r\nPositioning System (GPS) or the future European satellite navigation system Galileo.Multipath is generally considered undesirable\r\nin the context of GNSS, since the reception of multipath can make significant distortion to the shape of the correlation function\r\nused for time delay estimation. However, some wireless communications techniques exploit multipath in order to provide signal\r\ndiversity though in GNSS, the major challenge is to effectively mitigate the multipath, since we are interested only in the satellitereceiver\r\ntransit time offset of the Line-Of-Sight (LOS) signal for the receiver�s position estimate. Therefore, the multipath problem\r\nhas been approached from several directions in order to mitigate the impact of multipath on navigation receivers, including the\r\ndevelopment of novel signal processing techniques. In this paper, we propose a maximum likelihood-based technique, namely,\r\nthe Reduced Search Space Maximum Likelihood (RSSML) delay estimator, which is capable of mitigating the multipath effects\r\nreasonably well at the expense of increased complexity. The proposed RSSML attempts to compensate the multipath error\r\ncontribution by performing a nonlinear curve fit on the input correlation function, which finds a perfect match from a set of ideal\r\nreference correlation functions with certain amplitude(s), phase(s), and delay(s) of the multipath signal. It also incorporates a\r\nthreshold-based peak detection method, which eventually reduces the code-delay search space significantly. However, the downfall\r\nof RSSML is the memory requirement which it uses to store the reference correlation functions. The multipath performance of\r\nother delay-tracking methods previously studied for Binary Phase Shift Keying-(BPSK-) and Sine BinaryOffset Carrier- (SinBOC-)\r\nmodulated signals is also analyzed in closed loop model with the new Composite BOC (CBOC) modulation chosen for Galileo E1\r\nsignal. The simulation results show that the RSSML achieves the bestmultipath mitigation performance in a uniformly distributed\r\ntwo-to-four paths Rayleigh fading channel model for all three modulated signals.
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