The well-known Space-Alternating Generalized Expectation Maximisation (SAGE) algorithm has been recently considered for\r\nmultipath mitigation in Global Navigation Satellite System (GNSS) receivers. However, the implementation of SAGE in a GNSS\r\nreceiver is a challenging issue due to the numerous number or parameters to be estimated and the important size of the data to\r\nbe processed. A new implementation of the SAGE algorithm is proposed in this paper in order to reach the same efficiency with a\r\nreduced complexity. This paper focuses on the trade-off between complexity and performance thanks to the Cramer Rao bound\r\nderivation. Moreover, this paper shows how the proposed algorithm can be integrated with a classical GNSS tracking loop. This\r\nsolution is thus a very promising approach for multipath mitigation.
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