Enhancing MIMO Array Imaging Quality

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Abstract

For radar imaging, resolution and dynamic range are two critical metrics to measure image quality. MIMO array exploits the spatial diversity of transmitters and receivers to achieve high cross-range resolution with fewer antennas than array-based imaging.
Generally, to make full use of the sparsity, at least the transmit array or the receive array does not satisfy the Nyquist sampling criterion. Therefore, the grating lobes may occur, which would produce ghost targets and submerge the weak targets. For far-field imaging, the grating lobes can be eliminated with various array design methods. In contrast, it cannot be completely eliminated for near-field imaging applications. Besides, the high sidelobes would also mask the weak targets and reduce the image's dynamic range. The traditional weighting method can effectively suppress the sidelobes, but the mainlobe resolution would be reduced.
In this thesis, we propose a method based on the spatially variant apodization method to enhance the image quality of near-field 1-D and 2-D MIMO array imaging. According to the generalized matched filtering imaging method, we can individually analyze the wavenumber spectrum in the cross-range and range directions of the transmit array and the receive array. Then the method can be easily implemented in the space domain to suppress the sidelobes and grating lobes without sacrificing the cross-range and range resolution. Moreover, three acceleration approaches are proposed to reduce the computation burden.
Both numerical simulation and experimental validation indicate that the proposed method can effectively suppress the sidelobes and grating lobes without spreading the mainlobe. Moreover, the acceleration methods can suppress the sidelobe and grating lobe level meanwhile decrease the processing time remarkably under some conditions.