Research on The Algorithm of Multi-Autonomous Underwater Vehicles Navigation and Localization Based on The Extended Kalman Filter

The technology of navigation and localization for Multi-Autonomous Underwater Vehicles (AUVs) is an important way to solve the problem of complex operation environment. This paper addresses the problem of Multi-AUVs cooperative navigation and localization, based on the Leader-Fellow form. Then, Extended Kalman Filter (EKF) algorithm is proposed to solve this problem. A navigation model of the slave AUV is established, using the kinematic equations of the slave AUV and the measurement equations based on the distance between the master AUV and the slave AUV. The proposed algorithm-EKF proves to be effective if applied to the nonlinear model and avoids the filtering divergence problem by linearizing the nonlinear equations. The simulation shows the feasibility of the EKF algorithm for Multi-AUVs cooperative navigation and localization and achieves a satisfying accuracy improvement compared to the conventional Kalman Filter (KF) algorithm.