Fast and accurate UWB radar imaging using hybrid of Kirchhoff migration and Stolt's F-K migration with inverse boundary scattering transform

Abstract

A fast and accurate radar imaging algorithm is proposed that is a hybrid of the Kirchhoff migration and Stolt's frequency-wavenumber (F-K) migration. The latter is known as a fast imaging method in the F-K domain using the fast Fourier transform. Kirchhoff migration is reported to be more accurate than Stolt's F-K migration, but requires locating reflection points. For this reason, Kirchhoff migration must be processed in the time domain, which can be extremely time-consuming. This study overcomes this hurdle by combining these two algorithms by introducing the texture angle and the inverse boundary scattering transform. These two tools enable the location of a reflection point to be determined quickly for each pixel of a radar image. Using the estimated locations, radar signals are modified according to the Kirchhoff integral. Then Stolt's F-K migration is applied to the modified signals to obtain an accurate radar image. To demonstrate the performance of the proposed method, the conventional Kirchhoff migration, Stolt's F-K migration and the proposed method are applied to a measured dataset.