Paper Number: 215

Date: Tuesday, 11 July 2006

Time: 11:20

Duration: 20 minutes

Session: Nonlinear Filtering I

Location: Bargello

 

Measurement Gaussian Sum Mixture Target Tracking

          Darko Musicki

          Robin Evans

 

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 Bayessian 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.