Underwater Pure Orientation Target Tracking Based on Adaptive Box Length KLD PF Algorithm

Aiming at the characteristics of underwater pure orientation target tracking, an adaptive box length Kullback-Leibler Distance (KLD) Particle Filter (PF) algorithm is proposed based on traditional adaptive KLD PF algorithm. When performing underwater pure orientation target tracking, the traditional adaptive KLD sampling may have a problem that the filtering accuracy is reduced or even invalid due to the fixed length of the KLD box. In the algorithm proposed in this paper, the length of the KLD box can be automatically adjusted according to the current particle distribution range, which can well solve the problem of precision degradation caused by the fixed KLD box length of the traditional adaptive KLD algorithm. The effectiveness of the adaptive box length KLD PF algorithm is verified by comparison with the traditional KLD PF algorithm in simulation. In this simulation, the adaptive box length KLD PF algorithm can effectively adapt to the changing environment of underwater tracking and has good tracking performance.

Abstract licence: CC BY-NC-ND

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.