A COMPARATIVE STUDY OF MONTE-CARLO METHODS FOR MULTITARGET TRACKING

被引：0
|
作者：
Septier, Francois [1 ]
Cornebise, Julien [2 ]
Godsill, Simon [3 ]
Delignon, Yves [1 ]
机构：
[1] Inst TELECOM TELECOM Lille1, Signal Proc Grp, Lille, France
[2] Univ British Columbia, Dept Comp Sci, Vancouver, BC V5Z 1M9, Canada
[3] Univ Cambridge, Signal Process Lab, Cambridge CB2 1TN, England
来源：
2011 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP) | 2011年
关键词：
Tracking; Monte-Carlo methods; Particle filter; MCMC; INFERENCE; MODELS;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, we address the problem of tracking an unknown and time varying number of targets and their states from noisy observations available at discrete intervals of time. Attention has recently focused on the role of simulation-based approaches, including Monte Carlo methods, in solving multitarget tracking problem, as these methods are able to perform well for nonlinear and non-Gaussian data models. In this paper, we present a comparative study of several Monte-Carlo methods in terms of estimation quality and complexity.
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页码：205 / 208
页数：4
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