ANALYSIS OF MULTIFRAME TARGET DETECTION USING PIXEL STATISTICS

Current track before-detect (TBD) algorithms are developed and analyze d using a path statistic for each potential object trajectory. However this path statistic does not characterize overall performance gain. W e propose a pixel-based statistic. This allows the TBD approach to be characterized as an image enhancement algorithm with detection gains c ompared with single frame detections. It is shown that for the TBD app roach to have superior detection over single frame detection the targe t signal lo noise ratio (SNR) must be greater than a threshold SNR in order to overcome the uncertainty in the target path. Tradeoffs are ma de for a class of velocity constrained target paths in terms of the de tection gain with respect to the maximum target velocity and number of frames integrated.