A Particle Filter Track-Before-Detect Algorithm Based on Hybrid Differential Evolution

Algorithms

Chaozhu Zhang²  Lin Li¹  Yu Wang² 

[1] Department of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China;

关键词: track-before-detect;    particle filter;    hybrid differential evolution;   

DOI  :  10.3390/a8040965

来源: mdpi

【 摘 要 】

In this paper, we address the problem of detecting and tracking targets with a low signal-to-noise ratio (SNR) by exploiting hybrid differential evolution (HDE) in the particle filter track-before-detect (PF-TBD) context. Firstly, we introduce the Bayesian PF-TBD method and its weaknesses. Secondly, the HDE algorithm is regarded as a novel particle updating strategy, which is proposed to optimize the performance of the PF-TBD algorithm. Thirdly, we combine the systematic resampling approach to enhance the performance of the proposed algorithm. Then, an improved PF-TBD algorithm based on the HDE method is proposed. Experiment results indicate that the proposed method has better performance in detecting and tracking than previous algorithms when the targets have a low SNR.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.