AOA Based CKF Adaptive Algorithm for AUV Navigation

High precision navigation is an important prerequisite to realizing various functions of the Autonomous Underwater Vehicle (AUV). Observation noise is not fixed, and the uncertainty of observation noise would lead to the accumulation of navigation errors. Therefore, this paper proposes an Archimedes Optimization Algorithm (AOA) based Cubature Kalman Filter (CKF) adaptive navigation algorithm. The real experimental data of the self-developed underwater vehicle are processed to evaluate the performance of the algorithm. Experimental results show that the algorithm can improve the navigation accuracy compared with the traditional method.