Compressive Sensing Approach for the Anomalous Measurements Detection. Experimental and Comparison Results

Lev Rapoport

Peer Reviewed

Abstract:	In this paper we use the ideas of the compressive sensing approach for the problem of GNSS anomalous measurements detection and isolation. The recently developed approach to decoding and error correction via linear programming is applied to the outliers mitigation problem [1-3]. New efficient algorithms for outliers detection are proposed. In the earlier work [4] two new algorithms were applied to the problem of cycle slips detection and isolation in carrier phase measurements. Experimental results show effectiveness of the proposed approach showing both good performance and low computational complexity, which is especially significant for real time applications.
Published in:	Proceedings of the 28th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2015) September 14 - 18, 2015 Tampa Convention Center Tampa, Florida
Pages:	2605 - 2615
Cite this article:	Rapoport, Lev, "Compressive Sensing Approach for the Anomalous Measurements Detection. Experimental and Comparison Results," Proceedings of the 28th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2015), Tampa, Florida, September 2015, pp. 2605-2615.
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