Title :
Study of Multi-target Tracking and Data Association Based on Sequential Monte Carlo Algorithm
Author :
Lin-bo, Fan ; Li, Kang ; Ying-cheng, Wu ; Ming, Zhao
Author_Institution :
Inst. of Reliability Eng., Guizhou Univ., Guiyang
Abstract :
A new method based on sequential Monte Carlo algorithm is proposed for tracking multi-target and data association in non-linear system. The algorithm partitions the problem of multi-target tracking into two problems: single target tracking and data association. Single target tracking is implemented by using UKF and data association by using sequential Monte Carlo algorithm. Since Particle Filter has advantages in non-linear non-Gauss system, the proposed method performs well in the experiment.
Keywords :
Kalman filters; Monte Carlo methods; particle filtering (numerical methods); sensor fusion; target tracking; UKF; data association; multitarget tracking; nonlinear nonGauss system; particle filter; sequential Monte Carlo algorithm; Monte Carlo methods; Nonlinear filters; Particle filters; Particle tracking; Partitioning algorithms; Reliability engineering; Seminars; State estimation; Target tracking; Taylor series; UKF; data association; particle filtering; target tracking;
Conference_Titel :
Future BioMedical Information Engineering, 2008. FBIE '08. International Seminar on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3561-6
DOI :
10.1109/FBIE.2008.73
