A Novel Prescreening Method for Land-Mine Detection in UWB SAR Based on Feature Point Matching

Abstract

Ultrawideband synthetic aperture radar (SAR) (UWB SAR) is a sufficient approach to detecting land mines over large areas from a safe standoff distance. UWB SAR detection involves three steps: imaging, prescreening, and discrimination. Many studies have concentrated on imaging and discrimination, whereas few have highlighted prescreening. We propose a novel prescreening method for extracting the region of interest from an entire SAR image. The proposed method is based on feature point matching in contrast to traditional approaches, which are based on the constant false alarm rate (CFAR) technique. Our method incorporates knowledge on the electromagnetic scattering caused by land mines into the prescreening process and does not rely on clutter environments. Thus, the method more efficiently eliminates nonhomogeneous clutter than do CFAR-based methods and is more advantageous in processing large-area SAR images. The efficiency of the proposed method is validated by real data on an airship-mounted UWB SAR system.