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Improved Method for Single and Multiple GNSS Faults Exclusion based on Consensus Voting

Published online by Cambridge University Press:  27 February 2019

Qieqie Zhang ,
Long Zhao  and
Jianhua Zhou
Qieqie Zhang
Affiliation:
(Science and Technology on Aircraft Control Laboratory, Beihang University, Beijing 100191, China) (Digital Navigation Center, Beihang University, Beijing 100191, China)
Long Zhao*
Affiliation:
(Science and Technology on Aircraft Control Laboratory, Beihang University, Beijing 100191, China) (Digital Navigation Center, Beihang University, Beijing 100191, China)
Jianhua Zhou
Affiliation:
(Science and Technology on Aircraft Control Laboratory, Beihang University, Beijing 100191, China) (Digital Navigation Center, Beihang University, Beijing 100191, China) (Beijing Satellites Navigation Center, Beijing 100094, China)
*
(E-mail: [email protected])
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Abstract

Receiver Autonomous Integrity Monitoring (RAIM) provides an integrity service for Global Navigation Satellite Systems (GNSS). The conventional RAIM algorithm is based on the assumption of a single fault and typically uses the forward-backward method, which is based on the w-test or correlation analysis methods, to exclude the faults. It is suitable for single fault detection and exclusion, while it can lead to inefficiency, can be misleading and can even fail in the exclusion of multiple faults. To solve this problem, an improved method based on consensus voting of the w-test and correlation analysis methods is presented. To verify the performance of the improved method, tests using Global Positioning System (GPS)/BeiDou System (BDS) data have been carried out in comparison with the conventional methods in terms of false and correct faults exclusion rate and computational complexity in the case of a different number of faults. Results show that the improved method has almost the same correct exclusion rate compared to the conventional RAIM in the case of a single fault. It is worth noting that the improved method has a higher correct exclusion probability and computational efficiency as well as a lower possibility of false exclusion in the case of multiple faults.

Keywords

GNSSRAIMFault detection and exclusionMultiple faultsConsensus voting
Type
Research Article
Information
The Journal of Navigation , Volume 72 , Issue 4 , July 2019 , pp. 987 - 1006
Copyright
Copyright © The Royal Institute of Navigation 2019 

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