Abstract

This paper presents application of an efficient sparse image reconstruction using total variation minimization (TVM) for multiple-input multiple-output (MIMO) ground penetrating radar (GPR). The halfspace Green's function is efficiently evaluated with saddle point method and is incorporated in the beamformer to take into account subsurface wave propagation. TVM minimizes the gradient of the image resulting in better edge preservation and shape reconstruction than the standard L1-minimization based Compressive Sensing. The number of antenna elements and frequency measurements in the MIMO radar system can be significantly reduced using the proposed approach without a significant degradation of the image quality.

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