Doppler Velocity Enhanced Range Migration Algorithm for High Resolution and Noise-Robust Three-Dimensional Radar Imaging

Millimeter-wave and microwave short-range radar are among the most promising environmental sensing methods, with applications to situations that are otherwise optically invisible. This paper presents a Doppler velocity-enhanced range migration algorithm (RMA) that achieves both high spatial resolution and low-complexity three-dimensional (3-D) radar imaging. In this method, we address the problem of human body recognition with motion using the assumption that the motion of different human parts generates distinct micro-Doppler variations in the radar data. These variations could not only separate the RMA images with different Doppler velocities in a coherent integration-based radar imaging process, but enhances a noise reduction effect by decomposing in the Doppler velocity space. To achieve a low complexity in 3-D imaging, we incorporate the RMA method and Doppler velocity-based data decomposition. The results of numerical and experimental tests on a realistic human phantom with a walking motion demonstrate that our method provides more informative and highly separated 3-D images, even in much low SNR situation.