MLPF algorithm for tracking fast moving target against light interference
Libo Zhang, Yuanqiang Cai, Zakir Ullah, Tiejian Luo · 2016
In order to deal with the difficulty of tracking the fast moving aerial targets with light interference, we propose an improved particle tracking algorithm named multi-layers particle filter (MLPF). In MLPF, the particles are divided into three categories: the main particles (M-particles), the subordinate particles (S-particles) and the regenerate particles (R-particles). In the phase of resampling and state estimating, only M-particles are involved, then the R-particles are generated and considered as new S-particles in the next cycle. To a certain extent, our algorithm maintains the diversity of particles and reduces the computation time. Besides, MLPF has significant improvements on overcoming the tracing error after the sudden disappearance of the target and solving the degradation of particles. We demonstrate effectiveness of our proposed algorithm through systematic experiments. Experimental results show MLPF has better tracking effect compared to the traditional particle filter (PF) when the target is moving fast and affected by light interference. In the first experiment, the running time has been reduced from 47s to 21s while the precision increased from 64% to 96%. And for the second experiment, the running time has been reduced from 237s to 121s while precision increased from 46% to 89%.