A New Adaptive Extended Kalman Filter for Cooperative Localization

Paper

A New Adaptive Extended Kalman Filter for Cooperative Localization

IEEE Transactions on Aerospace and Electronic Systems

Volume Number:

Issue Number:

Pages:

353

–

368

Publication Date:

February 2018

Yulong Huang; Yonggang Zhang; Bo Xu; Zhemin Wu; Jonathon Chambers

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Abstract

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.

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