Fast Background Subtraction for Through Obstacle Imaging Using a Low Cost, Portable Measurement System

Echoes from the obstacle or non-target objects in the imagery scene may suppress the target returns in radar imaging. Thus, a background subtraction procedure is required to enhance the target visibility. Since the conventional subspace or low rank and sparse decomposition methods require singular value decomposition (SVD) computations, in this study we investigate fast background subtraction methods which are more appropriate for field studies conducted by mobile devices. We obtain the low rank component using SVD free procedures using random matrices or reduce the dimension of the raw input prior to SVD calculations. A low-cost portable vector network analyzer (VNA) device and Vivaldi antenna pair are used in laboratory measurements. S21 measurements were used to obtain A-scans which are then concatenated to form B-scan image. The proposed fast methods have been compared to the conventional SVD as well as robust principal component analysis (RPCA). The results validate those similar performances have been achieved compared to RPCA with a % 30-85 decrease in running time.