Tracking of Crossing Targets with Passive Sensors

The textbook "Tracking of Crossing Targets with Passive Sensors" offers a comprehensive analysis of the methodology for tracking targets using passive image sensors. It addresses the tracking of the centroid of small, extended objects using measurements from a forward-looking infrared image sensor. The monograph presents the statistical characterization of the target's centroid and demonstrates that the offset measurement noise is autocorrelated. Additionally, state variable models and the corresponding filters for tracking the target centroid are introduced, with a comparison of their performance. Simulations show that filter models with autocorrelated measurement noise yield the best results. Furthermore, an algorithm for tracking crossing targets is presented, which utilizes measurements of the centroid and the offset measurement from the distributed image. The Joint Probabilistic Data Association Merged-Measurement Coupled Filter is employed for state estimation to perform coupled filtering for targets with common measurements.