An Integrity Monitoring Method for Multi-sensor Collaborative Navigation

Jun Xiong, Joon Wayn Cheong, Andrew G. Dempster, Zhi Xiong

Abstract: In this work we propose a cooperative integrity monitoring (CIM) method that cooperatively monitors the integrity for multi-sensor cooperative positioning (CP) systems. Based on the structure of decentralized Kalman filter, CIM is implemented via innovation decomposition method and cooperative innovation estimation. For innovation decomposition, this method introduces the concept of common and specific error sources for collaborators in a network. Referring to the cooperative innovation estimation, it is based on the concept of global and local innovations and the linearization model of inter-node measurements. Here, innovations of a single node are estimated cooperatively via a transformation relationship among global innovation, local innovation and whole innovation among all the collaborators. And the linearization model is used to analyze the observations from collaborators, which determines the variance of inter-node measurements during the computation of detection statistics. Lastly, in the stage of fault detection, due to the residual decomposition, we design two detection statistics (global and local) for the proposed method, and three possible criteria for fault detection. Using the vehicular CP as the background, a GNSS/UWB based CP systems in a vehicular Ad-hoc network (VANET) is simulated. Results show that, for GNSS integrity monitoring, the proposed CIM has obviously better fault detection ability than the traditional RAIM method. Also, the CIM has good sensitivity to the faulty UWB ranging measurements, which means that CIM can deal with the integrity monitoring of all the possible cooperative measurements.
Published in: 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)
April 20 - 23, 2020
Hilton Portland Downtown
Portland, Oregon
Pages: 461 - 468
Cite this article: Xiong, Jun, Cheong, Joon Wayn, Dempster, Andrew G., Xiong, Zhi, "An Integrity Monitoring Method for Multi-sensor Collaborative Navigation," 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS), Portland, Oregon, April 2020, pp. 461-468.
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