Measurement Gaussian Sum Mixture Target Tracking

Abstract

In this paper target tracking using measurements whose probability density function can be described (approximated) by a Gaussian sum mixture is described. The approach is illustrated for two classes of these measurements. One class is the measurements obtained by acoustic amplitude/time difference of arrival measurements typically obtained using motes. The other is measurements obtained by radar with large angular measurement errors. Such measurements in a cartesian system cannot be accurately modelled by a single Gaussian pdf. By following a Bayesian approach and the target existence paradigm, two target tracking filters have been derived. A variant of IPDA-the single scan target tracking filter, and a variant of the ITS-the multi scan target tracking filter, have been derived for situations when Gaussian sum measurements are available