Abstract
An appropriate measurement likelihood function is proposed from the measurement image model employed by most of the track-before-detect (TBD) approaches. Based on the likelihood function and a target motion model, we design an auxiliary particle filter-based Bayes multiframe method for detection and tracking a moving point target in infrared (IR) image sequences. Experimental results show its effectiveness for the detection and tracking of a low signal-to-noise ratio (SNR) point target.
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