A modified asynchronous sequential Kalman track fusion based on sound propagation time

Abstract

Abstract This paper presents a sequential Kalman asynchronous track fusion algorithm based on the effective sound velocity method proposed to deal with the problem of random asynchrony of multi-node measurement information in the distributed underwater multi-target detection system due to the propagation effect of the sound channel. This algorithm updates the time stamp of target information reported by each sensor by using the effective sound velocity method, so as to obtain the actual time when the target state information appears in the underwater acoustic channel. Then, according to the actual asynchronous situation of the multi-sensor, it uses the sequential filter algorithm to fuse the asynchronous sensors. The simulation results show that the algorithm can improve the positioning accuracy of the original algorithm, has a strong adaptability to sensor target loss and accuracy loss, and has a certain application value.

Keywords

• Asynchronous track fusion
• Distributed
• Sequential filter
• Effective velocity of sound method