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Cooperative Localisation of AUVs based on Huber-based Robust Algorithm and Adaptive Noise Estimation

Published online by Cambridge University Press:  05 March 2019

Xu Bo ,
Asghar. A. Razzaqi Open the ORCID record for Asghar. A. Razzaqi [Opens in a new window]  and
Liu Yalong
Xu Bo
Affiliation:
(College of Automation, Harbin Engineering University, Harbin, China)
Asghar. A. Razzaqi*
Affiliation:
(College of Automation, Harbin Engineering University, Harbin, China)
Liu Yalong
Affiliation:
(China Electronic Technology Group Corporation Twentieth Research Institute)
*
(E-mail: asghar.abbas.razzaqi@gmail.com)
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Abstract

In this paper, adaptive noise estimation is used along with a previously proposed Huber-based robust algorithm for cooperative localisation of Autonomous Underwater Vehicles (AUVs). The Huber-based robust cooperative localisation algorithm named Huber-based Iterative Divided Difference Filtering (HIDDF), proposed in our previous work, effectively achieved a robust result against abnormal measurement noise, enhanced the stability of the filtering algorithm and improved the performance of cooperative localisation state estimation. However, its performance could be significantly further improved if it could estimate the system's noise statistical properties online in real time and then adaptively adjust the filtering gain matrix accordingly. In this paper, a novel adaptive noise estimation algorithm is proposed based on a covariance matching method. The proposed algorithm is suitable for adaptively estimating Gaussian and non-Gaussian measurement as well as process noise. The efficacy of the proposed algorithm has been verified through simulation results. In order to further verify the effectiveness of the proposed algorithm in practical systems, lake tests were conducted. Then, based on offline test data, the performance of the cooperative positioning algorithm under dual-pilot and single-pilot schemes was simulated. The advantages and feasibility of the algorithm are analysed and compared through performance comparison. Cooperative localisation accuracy of the previously proposed Huber-based robust algorithm has been enhanced significantly when used with the proposed adaptive noise estimation algorithm.

Keywords

Cooperative LocalisationAdaptive Noise EstimationInertial NavigationAutonomous Underwater Vehicle (AUV)
Type
Research Article
Information
The Journal of Navigation , Volume 72 , Issue 4 , July 2019 , pp. 875 - 893
Copyright
Copyright © The Royal Institute of Navigation 2019 

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