MIMO-SAR Image Reconstruction Experiment Using Back-Projection Algorithm with Automotive Radar for ADAS Applications

Abstract

Synthetic aperture radar (SAR) imaging has numerous uses in surface mapping, civil infrastructure, remote sensing, and terrain monitoring. Despite the benefits of multiple input multiple outputs (MIMO) in automotive radars, they are primarily used to provide range, azimuth, and elevation information for automotive applications. Obtaining acceptable angular resolution for automotive radar is a recurring difficulty due to vehicle-to-vehicle, vehicle-to-ground, vehicle-to-guardrail, and vehicle-to-tunnel discrimination. The purpose of this work is to demonstrate MIMO-SAR for finer angular resolution utilizing the 77-GHz Texas Instruments (TI) frequency-modulated continuous wave (FMCW) AWR1642 radar. SAR and MIMO radar topologies are used to increase synthetic or virtual aperture while maintaining adequate angular resolution. SAR is used to rebuild images from experimental data, and the images are created using a backpropagation algorithm. The findings are presented for SAR, MIMO, and MIMO-SAR. Furthermore, the experimental demonstration of MIMO-SAR using 77 GHz automobile radar verifies the prior modeling results. In addition, MIMO-SAR has been shown to provide better angular resolution than SAR and MIMO approaches. This algorithm's superior performance makes it appropriate for the automotive industry to perform SAR imaging on ego-corner deployed short-range radars (SRR) to picture guard rails, crossing vehicles, and VRUs. © 2024 IEEE.