Target Tracking of UUV Based on Maximum Correntropy High-Order UGHF
Kai Zhang, Hongjian Wang, Honghan Zhang, Naifu Luo, Jingfei Ren
Abstract
Underwater target tracking with signal propagation delay is a major challenge. The widely-used unscented Gauss-Helmert filter (UGHF) algorithm shows good tracking performance in bearing-only filters with signal propagation delay. However, UGHF algorithm is a nonlinear filtering method based on 2-order unscented transformation (UT), which can only match the accuracy of the 3-order Taylor expansion term of Gauss-Hermite model (GHM). Moreover, UGHF is a Gaussian filter, and when the measurement noise presents non-Gaussian characteristics, the tracking accuracy will be reduced. In order to improve the tracking accuracy of underwater bearing-only target, this paper proposes a high-order UGHF (HOUGHF) algorithm using high-order UT instead of 2-order UT. In order to further improve the tracking accuracy of the tracking algorithm under non-Gaussian noise, in this paper, maximum correntropy criterion (MCC) is used to replace the original minimum mean square error (MMSE) to update HOGGHF’s posterior estimation. The maximum correntropy HOGGHF (MCHOGGHF) algorithm is proposed by using MCC based on Gaussian kernel function. At the same time, in order to deal with the change of measurement noise, a method of adaptive Gaussian kernel width is presented. Simulation and sea trial results show that the two algorithm are superior to UGHF algorithm and MCHOGGH algorithm is superior to HOGGHF algorithm in estimation accuracy under non-Gaussian noise.