Research on position prediction of manned sightseeing submarine based on Kalman filter algorithm

Aiming at the safety problem of manned sightseeing submarine, a position prediction method based on Kalman filter algorithm is proposed in this paper. First, the submarine topographic map and current distribution map of the submarine area were generated by ArcGIS software, and a continuous dynamic system model was established, and the influence of current on submarine movement was considered. Secondly, a preliminary algorithm model of the submarine is established, considering the motion state of the submarine in three-dimensional space, and the position of the submarine at different time points is calculated by kinematic formula. Finally, Kalman filter algorithm is used to optimize and predict the preliminary algorithm model, and the probability density map of submarine predicted position is generated by MATLAB programming, so as to realize the accurate prediction of submarine real-time position. The research results of this paper provide a strong support for improving the accuracy of submarine position prediction, and also provide a guarantee for the safe operation of submarines.