Title :
Mixed Labelling in Multitarget Particle Filtering
Author :
Boers, Yvo ; Sviestins, Egils ; Driessen, Hans
Author_Institution :
Thales Nederland B.V., Netherlands
fDate :
4/1/2010 12:00:00 AM
Abstract :
The so-called mixed labelling problem inherent to a joint state multitarget particle filter implementation is treated. The mixed labelling problem would be prohibitive for track extraction from a joint state multitarget particle filter. It is shown, using the theory of Markov chains, that the mixed labelling problem in a particle filter is inherently self-resolving. It is also shown that the factors influencing this capability are the number of particles and the number of resampling steps. Extensive quantitative analyses of these influencing factors are provided.
Keywords :
Markov processes; particle filtering (numerical methods); target tracking; JMTD; Markov chains; joint multitarget density; mixed labelling; multitarget particle filtering; multitarget tracking; track extraction; Bayesian methods; Electronic mail; Filtering; Labeling; Monte Carlo methods; Particle filters; Particle tracking; Radar tracking; Statistical distributions; Target tracking;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
DOI :
10.1109/TAES.2010.5461657