This paper studies Bayesian filtering techniques applied to the design of advanced delay tracking loops in GNSS receivers with multipath mitigation capabilities. The analysis includes tradeoff among realistic propagation channel models and the use of a realistic simulation framework. After establishing the mathematical framework for the design and analysis of tracking loops in the context of GNSS receivers, we propose a filtering technique that implements Rao-Blackwellization of linear states and a particle filter for the nonlinear partition and compare it to traditional delay lock loop/phase lock loop-based schemes. 1. Introduction Global Navigation Satellite Systems (GNSS) are the general concept used to identify those systems that allow user positioning based on a constellation of satellites. Specific GNSS are the well-known American GPS, the Russian GLONASS, or the forthcoming European Galileo. All those systems rely on the same principle: the user computes its position by means of measured distances between the receiver and the set of in-view satellites. These distances are calculated estimating the propagation time that synchronously transmitted signals take from each satellite to the receiver. Therefore, GNSS receivers are only interested in estimating the delays of signals which are received directly from the satellites, referred to as line-of-sight signal (LOSS), since they are the ones that carry information of direct propagation time. Hence, reflections distort the received signal in a way that may cause a bias in delay and carrier-phase estimations. Multipath is probably the dominant source of error in high-precision applications, especially in urban scenarios, since it can introduce a bias up to a hundred of meters when employing a 1-chip wide (standard) delay lock loop (DLL) to track the delay of the LOSS, which is a common synchronization method used in spread-spectrum receivers. This error might be unacceptable in many applications. Sophisticated synchronization techniques estimate not only LOSS parameters but those of multipath echoes. This results in enhanced, virtually bias-free pseudorange measurements. In this paper, we investigate multipath estimating tracking loops in realistic scenarios, where this effect is known to be severe. The analysis is driven in two directions. Firstly, a review of statistical characterization of the channel model in such situations is performed and a commercial signal simulator. Secondly, a novel multipath estimating tracking loop is discussed, providing details on the implementation, as well as
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