Millimeter wave Multiple Input Multiple Output Inverse Synthetic Aperture Radar Images of Automotive Targets

Prior works have demonstrated that inverse synthetic aperture radar (ISAR) images of automotive targets offer valuable information regarding the targets' shape, size, and trajectory. The images were obtained by processing single-channel wideband radar data. However, low signal-to-clutter-and-noise ratios (SCNR) limited the image quality. In this work, we examine how the image quality of automotive ISAR images can be improved by leveraging the multiple channel data available from commercially available millimeter wave automotive radars. Specifically, we exploit the multiple input multiple output (MIMO) radar signal processing framework for this purpose with three transmitting antennas and four receiving antennas using frequency-modulated continuous waveform (FMCW) at 77 GHz. We consider two MIMO configurations: time domain modulation (TDM), where the transmitters are turned on in a sequential pattern one at a time, and binary phase modulation (BPM), where all the transmitters are turned on together, and their transmissions are phase modulated. Subsequently, the data from the multiple receivers are integrated, and the corresponding ISAR images are obtained through range-Doppler processing. Finally, we compare the image quality of the resultant ISAR images obtained from these different frameworks. This work collects and processes the measurement data of multiple automotive targets using the Texas Instruments millimeter wave radar.