Near-Field MIMO-SAR Millimeter-Wave Imaging With Sparsely Sampled Aperture Data

Abstract

The primary challenge of a cost-effective and low-complexity near-field millimeter-wave (mmWave) imaging system is to achieve high resolution with a few antenna elements as possible. Multiple-input multiple-output (MIMO) radar using simultaneous operation of spatially diverse transmit and receive antennas is a good candidate to increase the number of available degrees of freedom. On the other hand, higher integration complexity of extremely dense transceiver electronics limits the use of MIMO only solutions within a relatively large imaging aperture. Hybrid concepts combining synthetic aperture radar (SAR) techniques and sparse MIMO arrays present a good compromise to achieve short data acquisition time and low complexity. However, compared with conventional monostatic sampling schemes, image reconstruction methods for MIMO-SAR are more complicated. In this paper, we propose a high-resolution mmWave imaging system combining 2-D MIMO arrays with SAR, along with a novel Fourier-based image reconstruction algorithm using sparsely sampled aperture data. The proposed algorithm is verified by both simulation and processing real data collected with our mmWave imager prototype utilizing commercially available 77-GHz MIMO radar sensors. The experimental results confirm that our complete solution presents a strong potential in high-resolution imaging with a significantly reduced number of antenna elements.