A SINS/DVL/USBL integrated navigation and positioning IoT system with multiple sources fusion and federated Kalman filter

Abstract The navigation and positioning subsystem offers important position information for an autonomous underwater vehicle (AUV) system. It plays a crucial role during the exploration operations of AUV. Many scholars research positioning. Various improved methods systems were presented. However, as diversity ocean environment, random drift gyroscope, error accumulation, variety tasks, other negative factors, results are uncertain incredible. accuracy, stability, robustness not guaranteed, which cannot meet increasing application requirement. Therefore, we put forward SINS/DVL/USBL integrated IoT system with multiple resource fusion federated Kalman filter. In this method, first present SINS/DVL combined filtering gain compensation strategy. So can enhance accuracy stability Secondly, proposed USBL acoustic signals to improve performance. Lastly, filter fuse from subsystem. Through three methods, robustness. Comprehensive simulation indicated feasibility effectiveness system, provides critical reference it also AUV achieve high efficiency tasks.