Affiliation:
1. School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
2. Hangzhou Innovation Institute, Beihang University, Hangzhou, China
Abstract
Autonomous navigation is one of the most critical technologies for ships. The initial alignment technology is the key to achieving autonomous navigation. However, the wind and waves on the sea seriously affect the initial alignment accuracy and even make it divergent. In this paper, a polarization navigation system/geomagnetic navigation system (PNS/GMNS)–assisted initial alignment method based on wind and wave disturbance model is proposed with applications of ships under wind and wave conditions. At the coarse alignment stage, a vector-weighted matching algorithm is designed in response to the difference in sensor measurement errors, which can solve the problem of error divergence in traditional methods. At the fine alignment stage, the proposed wind and wave disturbance model is introduced into the integrated navigation model. Subsequently, the Kalman filter is performed to estimate system states, which significantly improves the initial alignment accuracy. Finally, the effectiveness of the proposed method is verified by both simulation and experiment studies.
Funder
National Natural Science Foundation of China
National Key R&D Program of China
Hangzhou Science and Technology Major Innovation Projects