Fully adaptive space-spectral detection of small targets in the absence of a-priori knowledge of the spectral signature of the target

The ability to detect and track dim unresolved targets in heavy clutter can be improved by the inclusion of the spectral dimension. Because of the great variation in targets, operating conditions and environments factors the spectral signature of the target is typically unknown. This paper present a fully adaptive matched filter and tracking paradigm which assumes no a priori information about the spectral signature of the target. It is shown that the full SCR gain can be realized in the absence of the spectral signature of the target. The ROC curve of the detector is used to show that performance loss due to the absence of spectral information is entirely due to an increase in the false alarm probability. This increase in PFA adversely effects tracker performance. The SCR track feature is developed to mitigate these effects. Track features provide an information shunt around the detection threshold nonlinearity that would otherwise block the flow of useful information to the tracker.