A New Adaptive Extended Kalman Filter for Cooperative Localisation

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  2. Professor Jonathon Chambers
Author(s)Huang Y, Zhang Y, Xu B, Wu Z, Chambers JA
Publication type Article
JournalIEEE Transactions on Aerospace and Electronic Systems
Pagesepub ahead of print
ISSN (electronic)1557-9603
Full text is available for this publication:
To solve the problem of unknown noise covariance matrices inherent in the cooperative localization of autonomous underwater vehicles, a new adaptive extended Kalman filter is proposed. The predicted error covariance matrix and measurement noise covariance matrix are adaptively estimated based on an online expectation-maximization approach. Experimental results illustrate that, under the circumstances that are detailed in the paper, the proposed algorithm has better localization accuracy than existing state-of-the-art algorithms.
PublisherInstitute of Electrical and Electronics Engineers
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