Compressive sensing in through-the-wall radar imaging

High resolution through-the-wall radar imaging (TTWRI) demands wideband signals and large array apertures. Thus a vast amount of measurements is needed for a detailed reconstruction of the scene of interest. For practical TTWRI systems it is imperative to reduce the number of samples to cut down on hardware cost and/or acquisition time. This can be achieved by employing compressive sensing (CS). Existing approaches imply a point target assumption, which may not hold in practical applications. We apply a novel CS approach for TTWRI using the 2D discrete wavelet transform to sparsify images. In this fashion, we overcome the above stated limitation and are able to deal with extended targets. Experimental results show that high image qualities are obtained, similar to images generated using the full measurement set.