Lance KaplanSeung-Mok OhJames H. McClellan
This paper presents a novel scheme to detect and discriminate landmines from other clutter objects during the image formation process for ultra-wideband (UWB) synthetic aperture radar (SAR) systems. By identifying likely regions containing the targets of interest, i.e., landmines, it is possible to speed up the overall formation time by pruning the processing to resolve regions that do not contain targets. The image formation algorithm is a multiscale approximation to standard backprojection known as the quadtree that uses a 'divide-and- conquer' strategy. The intermediate quadtree data admits multiresolution representations of the scene, and we develop a contrast statistic to discriminate structured/diffuse regions and an aperture diversity statistic to discriminate between regions containing mines and desert scrub. The potential advantages of this technique are illustrated using data collected at Yuma, AZ by the ARL BoomSAR system.
R.C. DiPietroRonald L. FanteR. P. PerryM. SoumekhLaurens D. Tromp
Jeremy S. De BonetPaul ViolaJohn W. Fisher
Lance KaplanSeung-Mok OhJames H. McClellanRomain MurenziKamesh Namuduri