A Kalman Filter Model for Ship Navigation Accuracy Optimization

Abstract

Aiming at the problem of improving the navigation accuracy of ships, a Kalman filter algorithm based on optimization is proposed for navigation optimization. On the basis of studying the dead reckoning knowledge, we establish the dimensional dynamic equation of the ship integrated navigation system. Then the extended Kalman filter is adjusted by using fuzzy logic adaptive controller (FLAC) and it is applied to GPS/INS information fusion to enable it to have adaptive ability to deal with environment disturbance. Finally, the method is used to simulate the GPS/INS integrated navigation system on MATLAB platform. The results show that the improved model can effectively use part of the system data to update and iterate, and improve the stability and reliability of the filter, so it is also better suitable for ship navigation and target tracking.