Title :
A Linear Inverse Scattering Algorithm for Radar Imaging in Multipath Environments
Author :
Gennarelli, G. ; Soldovieri, Francesco
Author_Institution :
Inst. for the Electromagn. Sensing of the Environ., Naples, Italy
Abstract :
This letter deals with the electromagnetic imaging in the presence of multipath propagation of interest for through-wall and urban sensing scenarios. The 2-D tomographic approach here presented combines a linear inverse scattering model, based on the Kirchhoff approximation, with the finite-difference time-domain (FDTD) technique. In particular, FDTD is exploited to evaluate the incident field and Green´s function in noncanonical scenarios, so that the kernel of the linear integral equation is completely built. After, an inversion scheme based on the truncated singular value decomposition is applied to obtain a regularized solution of the problem. Numerical results demonstrate that the proposed approach yields well-focused images free of multipath ghosts, thus allowing to discriminate the actual target position. Moreover, it permits to highlight the capabilities offered by multipath exploitation such as improved crossrange resolution and detection of targets in the non-line-of-sight region of the radar.
Keywords :
Green´s function methods; electromagnetic wave scattering; finite difference time-domain analysis; radar imaging; singular value decomposition; 2D tomography; Green function; Kirchhoff approximation; crossrange resolution; electromagnetic imaging; finite difference time-domain technique; linear inverse scattering algorithm; linear inverse scattering model; multipath environment; multipath propagation; non-line-of-sight region; radar imaging; regularized solution; target detection; through wall sensing; truncated singular value decomposition; urban sensing; Finite difference methods; Green´s function methods; Image reconstruction; Imaging; Inverse problems; Radar imaging; Time domain analysis; Finite-difference time domain (FDTD); linear inverse scattering; multipath propagation; urban sensing;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2012.2230314