Forward-Looking MIMO-SAR for Enhanced Radar Imaging in Autonomous Mobile Robots

Synthetic aperture radar (SAR) techniques are commonly used in spaceborne and airborne side-looking radar imaging applications, where the relatively high platform speeds enable the formation of very long synthetic apertures, which provide images with high angular resolution. However, the recent development of new autonomous ground vehicles, with relatively slow speeds, calls for new SAR imaging methods to obtain high angular resolution images. In this paper, the concept of forward-looking multiple-input multiple-output SAR (FL-MIMO-SAR) is analyzed and applied for short-range millimeter-wave radar forward-looking imaging in autonomous mobile robots (AMRs). Moreover, if the antenna inter-element spacing in the MIMO array is small, the FL-MIMO-SAR imaging system will provide low or no angular resolution refinement at the radar boresight region, i.e., Doppler beam sharpening (DBS) ineffective region. To solve that, the combination of FL-MIMO-SAR and sparse MIMO arrays with large inter-element spacing (FL-sparseMIMO-SAR) is proposed. Aspects such as the signal model, image reconstruction, complexity reduction, and the left-right ambiguity for FL-MIMO-SAR imaging systems are addressed. In addition, different imaging scenarios for AMRs are simulated using a frequency-modulated continuous wave radar simulator. Simulation results are validated with real measurements. It is shown that the proposed combination of FL-MIMO-SAR and MIMO arrays with large inter-element spacing manages to significantly suppress the grating lobes, which come from the sparsity in the antenna array. Moreover, the proposed FL-sparseMIMO-SAR helps to relax the requirements on the synthetic aperture length and solves the DBS-blind region problem, thanks to the larger real sparse MIMO array and the grating lobes suppression with the FL-SAR processing. Finally, the results show high potential for radar imaging systems, with FL-sparseMIMO-SAR capabilities, to be employed in the applications of AMRs towards smart factories and warehouses.