<title>Spatiotemporal multiscan adaptive matched filtering</title>

Abstract

Detecting the presence of small weak targets in nonstationary clutter backgrounds is a fundamental problem in representative IR surveillance and tracking systems. In this paper, a system is proposed using spatiotemporal adaptive matched filtering to suppress the effects of clutter and enhance target detection. Shortfalls in conventional adaptive systems lead to a multiple parallel scanning approach to eliminate transients resulting from suboptimal filtering at clutter edges. Simulation results are provided which demonstrate that this approach provides substantially superior performance to a non-adaptive matched filter detection system design using global clutter statistics and, in some cases, can even achieve performance approximating that of an ideal fully-adaptive detector design from the complete statistical knowledge of the nonstationary clutter.