A New Adaptive Extended Kalman Filter for Cooperative Localization

Authors: Yulong Huang, Yonggang Zhang, Bo Xu, Zhemin Wu, Jonathon A. Chambers - IEEE Transactions on Aerospace and Electronic Systems 2017 cited by 291

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.