Compressive sensing using approximated total variant transform to reduce the required number of antennas in radar-based medical imaging

Cempressive sensing (CS) technique is usually used to reconstruct the original signal (full-sampled signal) from using under-sampled signal. Based on the CS theory, the original signal can be reconstructed by using fewer signal samples which is obtained from a random measurement matrix. In this work, a CS algorithm using approximated total variant transform is used to reconstruct clear images in radar-based microwave imaging aimed at medical applications using only small number of antennas. The proposed approach is successfully tested via numerical simulations on a head imaging environment