Millimeter-Wave Imaging With Accelerated Super-Resolution Range Migration Algorithm

Millimeter-wave imaging systems are increasingly used in human screening at checkpoints, in linear or multi-input multi-output (MIMO) array modes. Rather than pressing intrinsic system requirements to improve image quality, it seems more economical to appeal to some specific approaches, for example, super-resolution (SR) techniques. In this paper, as a variation of SR, coherence factor (CF) is incorporated in the framework of the range migration algorithm (RMA), termed CF-RMA for short. As a critical part of CF, the double integral in the wavenumber domain is approximated by a single integral in the sense of the point-matching method, resulting in a particular formulation to carry on another independent RMA program. Being computationally efficient, the proposed method is shown to be effective in suppressing sidelobes and background noise. The resolution (as gauged by the width of the main lobe of the point spread function) is enhanced as well. A structural similarity (SSIM) index is employed to quantify the image quality enhancement with respect to state-of-the-art SR approaches. In terms of computation load, the new approach is shown to be much more efficient than state-of-the-art SR approaches.