Research on AUV Integrated Navigation Method Based on Improved Particle Filter Algorithm

摘要

In view of the problem that GPS navigation equipment cannot be used underwater, the integrated navigation method which is based on the strap-down inertial navigation system (SINS) and long-base line (LBL) positioning system with buoys network are researched in this paper. The mathematical model of SINS/LBL integrated navigation system is established, and the integrated navigation method which is based on Rao—Blackwellised adaptive particle is researched, which dynamically reduces the particle number through the Euclidean distance and the cost function between particles. The simulation analysis of SINS/LBL integrated navigation shows that, compared with the standard particle filter algorithm, the Rao—Blackwellised adaptive particle filter algorithm is higher accuracy in position error estimation, and the number of particles is less, so it can be solved the state estimation problem of high-dimensional integrated navigation system.