Moving target’s detection performances in a sequence of infrared multispectral images

The paper deals with the detection performance of a moving target in multispectral IR image sequences with lowSNR. In this context, track-before-detect (TBD) is the generally used method, which consists in accumulating raw images over time to track before detect. For each target hypothesis (position, velocity, amplitude), the signal is integrated over time. In this way, the potential target with the best spatio-temporal correlation will be a candidate for a detection test. In this paper, we develop a minimum detection bound regardless of the TBD method used. Specifically, this bound gives the minimum average number of multispectral images required to detect the target.