Analysis of multiframe target detection using pixel statistics

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