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Analysis of target detection probability in sequence image

The detection of infrared small and puny target is the critical problem for target tracking and recognition based on imaging sensors. Being limited to the complicated environment factors, measurement scale and precision of the sensors, the measurements are uncertain, imprecise or incomplete on certain level, and thus brings the difficulty for detecting target in real image. Usually the binary hypothesis method is used to examine the potential target from background in a single frame, then the detection probability can be raised and the false alarm probability can be reduced through the method of detection multiframe of the sequence image (namely K/N rule). In this paper, the target detection probability Pd and the false alarm probability Pf for a single image is calculated on the basis of the probability density function p(ZH0) and p(ZH1) on judgment regions Z0 and Z1. In N times measurement of a sequence image, the target is detected at least K times, then it can determine that the target is existent. The Pd and Pf of K/N rule are analyzed according to single frame. Applying K/N rule, the detecting probability and the false alarm probability can meet the demands of the system if choosing the value of N and K properly.