ANFIS-EKF-Based Single-Beacon Localization Algorithm for AUV

Singe-beacon localization technology can help Autonomous Underwater Vehicles (AUVs) to obtain precise positions by deploying only one beacon. It is considered as a promising way, benefiting from saving much time and labor compared with traditional Long-Baseline Localization (LBL). A typical single-beacon scheme contains two essential questions: the initial observability problem long-endurance trajectory tracking problem. Aiming at these core problems, comprehensive solution for described in this paper. An multi-hypothesis position discriminant method proposed firstly, which helps achieve accurate location based on analysis. Then, an Adaptive Network Fuzzy Inference System (ANFIS)-improved Extended Kalman Filter (EKF) proposed, measuring information fused off-the-shelf sensors, including DVL, Compass, etc. ANFIS-EKF improve precisions restraining heavy loss of linearization conventional EKF. Both simulation field tests are conducted verify performance algorithms.