Abstract
The well-known Space-Alternating Generalized Expectation Maximisation (SAGE) algorithm has been recently considered for multipath mitigation in Global Navigation Satellite System (GNSS) receivers. However, the implementation of SAGE in a GNSS receiver is a challenging issue due to the numerous number or parameters to be estimated and the important size of the data to be processed. A new implementation of the SAGE algorithm is proposed in this paper in order to reach the same efficiency with a reduced complexity. This paper focuses on the trade-off between complexity and performance thanks to the Cramer Rao bound derivation. Moreover, this paper shows how the proposed algorithm can be integrated with a classical GNSS tracking loop. This solution is thus a very promising approach for multipath mitigation.
Highlights
In Global Navigation Satellite System (GNSS) applications, multipath (MP) errors are still one of the major error sources for conventional receivers
The additional signal replicas due to reflections on the local environment introduce a bias in the delay lock loops (DLLs), which leads to a positioning error [1, 2]
In order to reach the efficiency of the Space-Alternating Generalized Expectation Maximisation (SAGE) algorithm with a reduced complexity, and to keep the compatibility with conventional GNSS tracking loops (DLL/PLL), we proposed a new implementation of SAGE in [10]
Summary
The well-known Space-Alternating Generalized Expectation Maximisation (SAGE) algorithm has been recently considered for multipath mitigation in Global Navigation Satellite System (GNSS) receivers. The implementation of SAGE in a GNSS receiver is a challenging issue due to the numerous number or parameters to be estimated and the important size of the data to be processed. A new implementation of the SAGE algorithm is proposed in this paper in order to reach the same efficiency with a reduced complexity. This paper focuses on the trade-off between complexity and performance thanks to the Cramer Rao bound derivation. This paper shows how the proposed algorithm can be integrated with a classical GNSS tracking loop. This solution is a very promising approach for multipath mitigation
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