一种新型的水下地磁/声学/惯性融合导航算法

As the existing geomagnetic matching algorithms still face the problems of low positioning accuracy and high false match rate in underwater applications, a novel underwater geomagnetic/acoustic/inertial fusion navigation algorithm is proposed to further improve the underwater positioning accuracy of geomagnetic matching. First, the inertial navigation indication trajectory is rigidly transformed by regularly updated acoustic range information to obtain a coarse matching trajectory. Then, the improved genetic algorithm and taboo search algorithm are used to reconstruct and update the trajectory, and the Kalman filter is used for fusion and correction to obtain a precise matching trajectory. The simulation results show that the proposed algorithm can effectively improve the positioning accuracy compared to the traditional ICCP algorithm and genetic algorithm, and further reduce the algorithm complexity compared to the traditional ICCP algorithm. The support of acoustic range information can play a role in improving the positioning accuracy and calculation speed in the proposed algorithm.