Infrared Target Tracking with AM-FM Consistency Checks

Challenging infrared data sequences such as the well-known AMCOM closure sequences are characterized by highly nonstationary evolutionary target and clutter signatures, poor target-to- clutter ratios, and complex kinematics arising from both the target motion and the motion of the sensor platform itself. In such cases, track consistency checks can provide a valuable means for detecting an imminent track loss. In this paper, we consider a simple target model with a correlation-based detection process and a straightforward SIR particle filter track processor. We show that the performance of the track processor can be dramatically improved by incorporating modulation domain consistency checks to identify failure in the correlation-based detection process. This strategy results in a robust dual-domain tracker that, despite the simplicity of its state model, delivers superior tracking performance against the very difficult AMCOM sequences.