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Hier finden Sie wissenschaftliche Publikationen aus den FraunhoferInstituten. Boxparticle intensity filter
 Institution of Engineering and Technology IET: 9th IET Data Fusion & Target Tracking Conference, DF&TT 2012. CDROM : Algorithms & Applications, 16.17. May 2012, London, UK London: IET, 2012 ISBN: 9781849196246 ISBN: 1849196249 pp.3/13/6 
 Data Fusion & Target Tracking Conference (DF&TT) <9, 2012, London> 

 English 
 Conference Paper 
 Fraunhofer FKIE () 
Abstract
This paper develops a novel approach for multitarget tracking, called boxparticle intensity filter (boxiFilter). The approach is able to cope with unknown clutter, false alarms and estimates the unknown number of targets. Further more, it is capable of dealing with three sources of uncertainty: stochastic, settheoretic and data association uncertainty. The boxiFilter reduces the number of particles significantly, which improves the runtime considerably. The low particle number enables this approach to be used for distributed computing. A boxparticle is a random sample that occupies a small and controllable rectangular region of nonzero volume. Manipulation of boxes utilizes the methods from the field of interval analysis. Our studies suggest that the boxiFilter reaches an accuracy similar to a sequential Monte Carlo (SMC) iFilter but with much less computational costs.