Compressive Sensing-Based Two-Dimensional Diffraction Tomographic Algorithm for Through-the-Wall Radar Imaging

Abstract

Diffraction tomographic (DT) algorithm utilizes the Fast Fourier transform to achieve through-the-wall radar (TWR) imaging reconstruction and is suitable for real-time processing. High-resolution TWR imaging obtained by DT algorithm requires the wide signal bandwidth and large antenna array aperture, which makes the processing of the huge amount of measurement data very challenging. To solve the aforementioned algorithm, a compressive sensing (CS) based two-dimensional diffraction tomographic (DT) algorithm for TWR imaging is proposed in this paper. By exploiting the sparsity property of the echoes of concealed targets, the proposed imaging algorithm allows the random frequency sampling at each measurement position and recovers the missing frequency data through sparse reconstruction technique. Numerical simulation results have shown that the proposed CS-based DT algorithm can dramatically reduce the measured frequency data at each measurement position and provide the advantage in terms of enhancing the measurement speed without the loss of reconstruction quality.