Cooperative Navigation for Multi-AUVs Based on the Strong Tracking Filter and Embedded Cubature Kalman Filter

Cooperative navigation is regarded as a promising positioning technology for autonomous underwater vehicles (AUVs). This paper presents a modified method based on the Strong Tracking Filter (STF) and Embedded Cubature Kalman Filter (ECKF) for multi-AUV cooperative navigation. This method applies the STF to the traditional ECKF algorithm, effectively diminishing the error generated in the process of navigation when confronting the challenges of uncertain system models or system mutations. Simulations compare the modified method with two related traditional navigation methods and verily that our method maintains the highest positioning accuracy and stability under the adverse condition of system mutation. Compared with the ECKF algorithm, the positioning and heading angle errors derived from the modified method are reduced by 72.28% and 51.52%.