A variable structure multiple model particle filter for GMTI tracking

Abstract

The problem of tracking ground targets with GMTI sensors has received some attention in the recent past. In addition to standard GMTI sensor measurements, one is interested in using non-standard information such as road maps, and terrain-related visibility conditions to enhance tracker performance. The conventional approach to this problem has been to use the variable structure IMM (VS-IMM), which uses the concept of directional process noise to model motion along particular roads. In this paper, we present a particle filter based approach to this problem which we call variable structure multiple model particle filter (VS-MMPF). Simulation results show that the performance of the VS-MMPF is much superior to that of VS-IMM.