FISST Based Method for Multi-Target Tracking in the Image Plane of Optical Sensors

Sensors

Yang Xu¹  Hui Xu²  Wei An² 

[1] School of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China;

关键词: finite set statistics;    signal amplitude information;    PHD filter;    multi-target tracking;    Gaussian mixture;   

DOI  :  10.3390/s120302920

来源: mdpi

【 摘 要 】

A finite set statistics (FISST)-based method is proposed for multi-target tracking in the image plane of optical sensors. The method involves using signal amplitude information in probability hypothesis density (PHD) filter which is derived from FISST to improve multi-target tracking performance. The amplitude of signals generated by the optical sensor is modeled first, from which the amplitude likelihood ratio between target and clutter is derived. An alternative approach is adopted for the situations where the signal noise ratio (SNR) of target is unknown. Then the PHD recursion equations incorporated with signal information are derived and the Gaussian mixture (GM) implementation of this filter is given. Simulation results demonstrate that the proposed method achieves significantly better performance than the generic PHD filter. Moreover, our method has much lower computational complexity in the scenario with high SNR and dense clutter.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland