Research Article
Cross-Entropy Based Data Association for Multi Target Tracking
@INPROCEEDINGS{10.4108/ICST.VALUETOOLS2008.4348, author={Daniel Sigalov and Nahum Shimkin}, title={Cross-Entropy Based Data Association for Multi Target Tracking}, proceedings={3rd International ICST Conference on Performance Evaluation Methodologies and Tools}, publisher={ICST}, proceedings_a={VALUETOOLS}, year={2010}, month={5}, keywords={data association target tracking heuristic optimization cross- entropy method Monte-Carlo methods}, doi={10.4108/ICST.VALUETOOLS2008.4348} }- Daniel Sigalov
Nahum Shimkin
Year: 2010
Cross-Entropy Based Data Association for Multi Target Tracking
VALUETOOLS
ICST
DOI: 10.4108/ICST.VALUETOOLS2008.4348
Abstract
Multiple-target tracking (MTT) in the presence of spuri- ous measurements poses difficult computational challenges related to the measurement-to-track data association prob- lem. Different approaches have been proposed to tackle this problem, including various approximations and heuristic op- timization tools. The Cross Entropy (CE) and the related Parametric MinxEnt (PME) methods are recent optimiza- tion heuristics that have proved useful in many combina- torial optimization problems. They are akin to evolution- ary algorithms in that a population of solutions is evolved, however the solution improvement mechanism is based on statistical methods of sampling and parameter estimation. In this work we apply the Cross-Entropy method and its recent MinxEnt variants to solve approximately the multi- scan version of the data association problem in the presence of misdetections, false alarms, and unknown number of tar- gets. We formulate the algorithms, and explore via simu- lation their efficiency and performance compared to other recently proposed algorithms.