Abstract:

This paper develops a systematic approach to track the centroid of a maneuvering target in image sequences based on the concept of Track while Detect. The statistical performance of centroid estimation with a strong Gauss noise background is studied. The authors clearly present the dilemma between performance of bias and variance when only binary transform or intensity bandpass processing is used. The suggested way for overcoming the difficulty is image pre-processing by spatial matched filtering when the shape is obtained. A simple and experimental method is found to predict the statistical performance of centroid estimation after matched filtering and segmentation. A new adaptive IMM algorithm called ATIMM is employed as the tracking filter and proved to satisfy the need of track while detect in a simulated low SNR image sequence, while the combination of matched filter, binary transform plus clustering, and ATIMM can achieve the best tracking performance.

Key words: cent ro id estim atio n, m aneuv ering t arg et tra cking, binary transform, spatial matched filter, adaptive int er activ e mult iple mo dels