A physics-based approach for detecting man-made objects in ultra-wideband SAR imagery

Abstract

We describe a physics-based approach for interpretation of ultra-wide and (UWB) synthetic aperture radar (SAR) imagery for object classification. The UWB sensor (50 MHz to 1 GHz) is used for detection of man-made objects, including those which are obscured by a forest canopy. An electromagnetic prediction is made illustrating that the “early-time” (physical optics) portion of the backscatter is highly dependent on aspect angle of the incident wave. At certain angles, man-made objects exhibit specular reflections while natural objects generally do not. Aspect-angle sensitivity is estimated by reconstructing the SAR image of an object over smaller subapertures of the full synthetic aperture. This multi-aperture approach provides important angular information, however, this alone cannot be used to accurately classify objects due to a limited range of aspect angles and an inhomogeneous obscuring media. Consequently this information is combined with polarization information to establish a robust feature vector for object classification