INS Aided Multi-GNSS Robust Positioning with Centralized and Distributed Fusion Algorithm

Baoyu Liu, Xingqun Zhan, Maolin Chen

Peer Reviewed

Abstract:	Recently, GNSS receiver commonly employs multiple GNSS signals for positioning, but simultaneously the risk of encountering with GNSS system fault that the multi-GNSS receiver embraces goes up. If any measurement from the multiple constellations is in fault, the multi-GNSS solution will be totally influenced. Integrity faults can be detected and isolated by various Receiver Autonomous Integrity Monitoring (RAIM) algorithms; however the faults with small amplitudes are difficult for RAIM to detect without augmentations, and it will be worse when there are only a few satellites are available. Based on the assumption of at most a single fault occurs in the multiple constellations at any given time, this paper presents a method which is able to detect single range bias fault of small amplitude and identify corresponding faulty satellite in the position domain, by treating each satellite system as an isolating sensor and estimating the difference vector between single-GNSS position solutions. A detailed failure detection and isolation (FDI) process is given; according to the estimated results, a conservative solution is obtained with centralized or distributed fusion algorithm even if the detected fault is impossible to be identified and compensated. Finally, simulation examples combine GPS with BDS are carried out to validate the presented method.
Published in:	Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016) September 12 - 16, 2016 Oregon Convention Center Portland, Oregon
Pages:	171 - 179
Cite this article:	Liu, Baoyu, Zhan, Xingqun, Chen, Maolin, "INS Aided Multi-GNSS Robust Positioning with Centralized and Distributed Fusion Algorithm," Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016), Portland, Oregon, September 2016, pp. 171-179. https://doi.org/10.33012/2016.14744
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