Title :
Research of improved probability data association algorithm for multi-target tracking
Author :
Zhengwang, Jia ; Yinya, Li ; Mingxiu, Mao ; Li, Chen ; Zhi, Guo
Author_Institution :
Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
An improved probabilistic data association is proposed to overcome both the drawback of complication in joint probabilistic data association and the unneutrality of multi-targets processing by probabilistic data association. It incorporates the radar Doppler measurement information and modifies weighting of state estimation of measurements in the common region, and then makes the final estimation more exact and improves further performance. The theoretical analysis and Monte-Carlo simulation results show that the algorithm has small computation cost and a better real-time tracking performance.
Keywords :
Doppler radar; Monte Carlo methods; sensor fusion; target tracking; Monte-Carlo simulation; multitarget tracking; multitargets processing; probabilistic data association; probability data association algorithm; radar Doppler measurement information; real-time tracking performance; state estimation; Algorithm design and analysis; Automation; Computational efficiency; Doppler measurements; Doppler radar; Performance analysis; Radar measurements; Radar tracking; State estimation; Data association; Multi-target tracking; Probabilistic data association algorithm;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5194908