Title :
A study on multitarget tracking with adaptive local linearisation particle filters
Author :
Kravaritis, G. ; Mulgrew, Bernard
Author_Institution :
Inst. for Digital Commun., Edinburgh Univ.
Abstract :
Over the last decade much research has been conducted on exploiting particle filtering techniques in the field of target tracking. Although the major body of the work in that area concerns tracking a single target, algorithms have also been proposed for the multiple target case. In most multitarget algorithms the state estimator is a basic particle filter (e.g. a sequential importance resampling filter) used in a complex multitarget structure. The contribution of this paper is the use of the more powerful local linearisation particle filter as the basic estimation tool, for the multitarget problem
Keywords :
importance sampling; linearisation techniques; matrix algebra; particle filtering (numerical methods); sequential estimation; state estimation; target tracking; adaptive local linearisation particle filters; multitarget tracking; sequential importance resampling filter; state estimator; Coordinate measuring machines; Equations; Filtering; Noise measurement; Particle filters; Particle tracking; Position measurement; Radar tracking; State estimation; Target tracking;
Conference_Titel :
Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on
Conference_Location :
Novosibirsk
Print_ISBN :
0-7803-9403-8
DOI :
10.1109/SSP.2005.1628790