Title :
Particle filtering for multi-target tracking using jump Markov systems
Author :
Ooi, Augustine ; Vo, Ba-Ngu ; Doucet, Arnaud
Author_Institution :
Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia
Abstract :
In multi-target tracking, one jointly estimates the number of targets and the individual target states from sensor measurements. This is a challenging problem due to the time varying number of targets and unknown measurement to target associations. We present a particle filtering method for multi-target tracking. The proposed method applies particle filtering techniques to a jump Markov system that models the multi-target dynamics. Simulation results using this particle method are also presented.
Keywords :
Markov processes; filtering theory; nonlinear filters; parameter estimation; sensor fusion; state estimation; target tracking; jump Markov systems; multi-target tracking; nonlinear filters; particle filtering; sensor fusion; target state estimation; Australia; Filtering; Particle filters; Particle tracking; Signal processing; Signal processing algorithms; State estimation; Target tracking; Time measurement; Time varying systems;
Conference_Titel :
Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004. Proceedings of the 2004
Print_ISBN :
0-7803-8894-1
DOI :
10.1109/ISSNIP.2004.1417450