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Volume 24
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10.3390/s24186042
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Article

Cubature Kalman Hybrid Consensus Filter for Collaborative Localization of Unmanned Surface Vehicle Cluster with Random Measurement Delay

by
Weicheng Liu
,
Jichao Yang
*,
Tongbo Xu
,
Xiaolei Ma
and
Shengli Wang
College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China
*
Author to whom correspondence should be addressed.
Sensors 2024, 24(18), 6042; https://doi.org/10.3390/s24186042
Submission received: 8 July 2024 / Revised: 30 August 2024 / Accepted: 16 September 2024 / Published: 18 September 2024
(This article belongs to the Section Navigation and Positioning)
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Abstract

This paper addresses the collaborative localization problem for unmanned surface vehicle (USV) clusters with random measurement delays. We propose a Cubature Kalman Hybrid Consensus Filter (CKHCF) based on the cubature Kalman filter (CKF) for widely distributed USV clusters lacking global communication capabilities. In this approach, each USV exchanges two pairs of information with all its neighbors and recalculates the received localization data based on distance and relative angle measurements. The recalculated information is then fused with the locally filtered data and updated to obtain localization information based on global measurements. To mitigate the impact of random measurement delays, we employ one-step prediction to compensate for delayed measurements. We present the derivation of the CKHCF algorithm and prove its consistency and boundedness using mathematical induction. Finally, we validate the effectiveness of the proposed algorithm through simulation experiments.
Keywords: cubature Kalman filter (CKF); cubature Kalman hybrid consensus filter (CKHCF); collaborative localization; random measurement delays cubature Kalman filter (CKF); cubature Kalman hybrid consensus filter (CKHCF); collaborative localization; random measurement delays

Share and Cite

MDPI and ACS Style

Liu, W.; Yang, J.; Xu, T.; Ma, X.; Wang, S. Cubature Kalman Hybrid Consensus Filter for Collaborative Localization of Unmanned Surface Vehicle Cluster with Random Measurement Delay. Sensors 2024, 24, 6042. https://doi.org/10.3390/s24186042

AMA Style

Liu W, Yang J, Xu T, Ma X, Wang S. Cubature Kalman Hybrid Consensus Filter for Collaborative Localization of Unmanned Surface Vehicle Cluster with Random Measurement Delay. Sensors. 2024; 24(18):6042. https://doi.org/10.3390/s24186042

Chicago/Turabian Style

Liu, Weicheng, Jichao Yang, Tongbo Xu, Xiaolei Ma, and Shengli Wang. 2024. "Cubature Kalman Hybrid Consensus Filter for Collaborative Localization of Unmanned Surface Vehicle Cluster with Random Measurement Delay" Sensors 24, no. 18: 6042. https://doi.org/10.3390/s24186042

APA Style

Liu, W., Yang, J., Xu, T., Ma, X., & Wang, S. (2024). Cubature Kalman Hybrid Consensus Filter for Collaborative Localization of Unmanned Surface Vehicle Cluster with Random Measurement Delay. Sensors, 24(18), 6042. https://doi.org/10.3390/s24186042

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