Experimental study on super-resolution 3-D imaging algorithm based on extended capon with reference signal optimization for UWB radars

Near field radar employing UWB (Ultra Wideband) signals with its high range resolution is promising as various sensing applications. It enables robotic or security sensors that can identify a human body in invisible situations. As one of the most promising radar algorithms, the RPM (Range Points Migration) is proposed. This offers an accurate 3-D (3-dimensional) surface extraction for various target shape. However, in the case of a complicated target surface whose variation scale is less than wavelength, it still suffers from image distortion caused by multiple interference signals with different waveforms. As a substantial solution, this paper proposes a novel range extraction algorithm by extending the Capon, known as frequency domain interferometry (FDI). This algorithm combines reference signal optimization with the original Capon to enhance the accuracy and resolution for an observed range into which a deformed waveform model is introduced. The results obtained from numerical simulations and an experiment prove that super-resolution UWB radar imaging is achieved by the proposed method, even for an extremely complex-surface target, including edges.