A New Variational Bayesian Adaptive Extended Kalman Filter for Cooperative Navigation

Sensors

Chengjiao Sun¹  Yonggang Zhang¹  Guoqing Wang¹  Wei Gao² 

[1] College of Automation, Harbin Engineering University, Harbin 150001, China;School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China;

关键词: extended Kalman filter (EKF);    variational Bayesian;    cooperative navigation;    nonlinear filters;   

DOI  :  10.3390/s18082538

来源: DOAJ

【 摘 要 】

To solve the problem of unknown state noises and uncertain measurement noises inherent in underwater cooperative navigation, a new Variational Bayesian (VB)-based Adaptive Extended Kalman Filter (VBAEKF) for master–slave Autonomous Underwater Vehicles (AUV) is proposed in this paper. The Inverse Wishart (IW) distribution is used to model the predicted error covariance and measurement noise covariance matrix. The state, together with the predicted error covariance and measurement noise covariance matrix, can be adaptively estimated based on VB approximation. The performance of the proposed algorithm is demonstrated through a lake trial, which shows the advantage of the proposed algorithm.

【 授权许可】

Unknown