A Compressed Sensing Stepped Frequency GPR Imaging Method in Ground Clutter Environment

Abstract

With the development of compressive sensing (CS) theory, considerable work have been done to apply CS to stepped frequency ground penetrating radar (SFGPR) imaging in order to reduce the data acquisition time and improve the image quality. However, in practical application, the imaging algorithm using CS approach will lose efficacy in strong ground clutter environment. In this paper, a CS SFGPR imaging reconstruction method combined with subspace projection clutter suppression approach is proposed to solve the above problem. All frequency domain data at each measurement position are reconstructed by CS measurement model at the first step. Then classic clutter suppression algorithms can be applicable to suppress the strong ground reflected wave. At the last step, orthogonal matching pursuit(OMP) algorithm is utilized to reconstruct the subsurface target image. Experiment results testify that the proposed CS SFGPR imaging method not only can reduce the data collection capacity for imaging but also can reconstruct the target image with less side lobe in strong ground clutter environment.