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