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.
A New Adaptive Extended Kalman Filter for Cooperative Localization
IEEE Transactions on Aerospace and Electronic Systems ; 54 , 1 ; 353-368
2018-02-01
1691046 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch