GROUND TARGET TRACKINGWITH ACOUSTICSENSORSUSINGPARTICLEFILTERS AND STATISTICALDATA ASSOCIATION MatsEkman'andNiclas Bergman 2
Saab Ab · 2006
Inthis paperthetracking ofground targets using acoustic sensors, distributed inawireless sensor network, isstudied. Since onlyacoustic sensors areutilized inthestudy the tracking problem canberegarded asa bearings-only application. Thesolution totheproblem isgiven within the Bayesian recursive framework, whereasequential Monte Carlomethodtotheground target tracking problem is developed. Theclassical sampling importance resampling (SIR) scheme isredesigned toalso track multiple targets. Theapproach forsolving thedataassociation problem is basedonhypothesis calculations according tothejoint probabilistic dataassociation (JPDA)method. Validation andevaluation ofthetracking algorithms areperformed using simulated data aswellasreal dataextracted froma ground sensor network.