Indoor Millimeter-Wave Imaging Based on Sparsity Estimated Compressed Sensing and Calibrated Point Spread Function

A compressed-sensing-augmented, sparsely-sampled indoor millimeter-wave imaging system is presented in this work. The system incorporates the proposed sparsity estimation prior to sub-sampling and a novel calibration procedure to process the point spread function (PSF) acquired from measuring a suspended point scatterer. The sparsity of the to-be-recovered radar echo spectrum is estimated with the dispersion relation of the waves, and the truncated singular value decomposition is utilized to denoise the PSF measured from the simple measurement scheme. Both methods are experimentally verified using an off-the-shelf 77-81 GHz frequency-modulated continuous-wave radar development board in conjunction with a mechanical scanner. Our low-cost imager yields promising results when the randomly kept samples are as few as 30% of the complete uniform measurements with a better-represented PSF for image reconstruction.