Bo Xu

TL;DR: Experimental results illustrate that the proposed adaptive extended Kalman filter has better localization accuracy than existing state-of-the-art algorithms.

TL;DR: In this article, a new outlier-robust Student's t based Gaussian approximate filter is proposed to address the heavy-tailed process and measurement noises induced by the outlier measurements of velocity and range in cooperative localization of autonomous underwater vehicles (AUVs).

TL;DR: It is proved that when the initial error and variance are small enough, the estimation error remains bounded and the performance difference between CKF and Unscented Kalman Filtering is the capture ability of the high items in the Taylor expansion.

TL;DR: The experimental results show that the proposed IMCCKF algorithm can effectively improve the positioning performance of CL system with measurement outliers and has the ability to adjust the KB in real time and quickly obtain the optimal value of the KB.

TL;DR: The experimental results show that ANFIS can effectively obtain the location of AUVs based on the input data when the communication packet is lost and the combination of the maximum correntropy criterion and the adaptive neuro-fuzzy inference system provides better positioning accuracy and robustness.