RF tomography based optimal linear filter

Abstract

Reconstructing high quality images of underground objects using ground penetrating radar (GPR) depends on method for 3D GPR data collection and processing. In this paper, we propose an accurate, fast method to reconstruct the image of underground targets using an optimal linear filter, such as matched filter processing. The match filter is the most common approach to simplify the solution of the inversion problem in GPR model. The proposed method is an optimal technical that increases the signal to noise ratio (SNR) to sharpen the quality of the image. Using this technique leads to decreased of reconstruction time. Also, it reduces the data acquisition time which is critical in most GPR applications. Compared with other algorithms, such as truncated singular value decomposition (TSVD) or algebraic reconstruction technique (ART), matched filter algorithms yield a high quality 2D image of shallowly buried objects faster and with minimal computational load or noise effect. Simulation results were carried out using the computational electromagnetic software FEKO and MATLAB, which demonstrate the effectiveness and feasibility of the proposed reconstruction method.