Automotive MIMO-SAR Imaging from Non-continuous Radar Acquisitions

Automotive Synthetic Aperture Radar (SAR) imaging is becoming increasingly relevant in the automotive industry thanks to its day and night, all-weather, and high-resolution imaging capabilities. The latter, in particular, is achieved by jointly processing several radar pulses. Since the vehicle where the radar is mounted is moving, each pulse illuminates the scene from a slightly different spatial location, generating bandwidth and, in turn, resolution. To achieve extremely fine resolutions, however, it is mandatory to use very long synthetic apertures; in other words, it is necessary to process all the radar pulses acquired on a very long portion of the vehicle's trajectory. Nevertheless, a radar that is fully compliant with the regulations must avoid a continuous transmission of pulses. The device transmits a burst of pulses, and then it must remain silent for a certain period. While this condition is not a problem for standard Multiple- Input Multiple-Output (MIMO) radar imaging, it is a big issue for synthetic aperture imaging. In the latter case, correct imaging can happen only when all the pulses sample uniformly the synthetic aperture, but this is impossible when pulses are transmitted on a non-uniform basis. Therefore, if we want to achieve extremely fine resolutions, we have to use very long apertures that are non-uniformly sampled. The uneven sampling generates gaps in the image spectrum with the consequent generation of side lobes. These side lobes in SAR images can eventually be mistaken for real targets triggering in this way unwanted maneuvers by an Advanced Driving Assistance System (ADAS). This work presents a novel method to eliminate side-lobes from high-resolution SAR images: the procedure starts by defining an ad-hoc reference system in which the spectral components of the image are independent of the position of the targets in the scene. This reference system also allows the description of the spectral gaps by a simple mono-dimensional function. After that, we exploit a well-known compressive sensing algorithm called CLEAN to remove side lobes. The proposed approach is validated using real data from an 8-channel automotive Radar operating in burst mode at 77 GHz. Results demonstrate the practical possibility of processing a synthetic aperture length as long as 2 meters, reaching outstanding angular resolutions.