An automatic framework using space-time processing and TR-MUSIC for subsurface imaging

Abstract

In this paper, we present an automatic framework combined space-time signal processing with Time Reversal electromagnetic (EM) inversion for subsurface multi-target imaging using Ground Penetrating Radar (GPR). This framework is composed of a Frequency-Wavenumber (FK) filter to suppress direct wave and ground bounce, a FK migration algorithm to automatically estimate the number of targets and identify target regions, which can be used to reduce the computational complexity of the following imaging algorithm, and a EM inversion algorithm using Time Reversal Multiple Signal Classification (TR-MUSIC) to reconstruct subsurface target. The feasibility of the framework is demonstrated with simulated data generated by GPRMAX.