DocumentCode
2838602
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
fYear
2009
fDate
17-19 June 2009
Firstpage
4919
Lastpage
4923
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/CCDC.2009.5194908
Filename
5194908
Link To Document