An Improved Deconvolution Algorithm for Sidelobe Suppression in Sparse Array SAR and MIMO Imaging Radars

A deconvolution algorithm to suppress the sidelobe and grating lobe effects in sparse array Synthetic Aperture Radars (SAR) and Multiple Input Multiple Output (MIMO) radars is proposed. To reduce the cost and complexity associated with large uniform arrays, sparsely populated arrays can be used. This introduces sidelobe and grating lobes effects that degrade the image quality. Knowing the point spread function, these undesirable effects can be suppressed using the proposed deconvolution algorithm. The algorithm comprises of 4 main steps: 1) Peak search, 2) Sweep and Extinguish, 3) Recursive Nulling and 4) Reconstruction. The basic idea is to find peaks and decorrelate them by recursively approximating their location and magnitude. The image quality after applying the algorithm is greatly improved at the cost of longer computation time. The algorithm is experimentally verified using a 31-element X-band circular array with a diameter of 30
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in scenarios with canonical targets and real-world targets. It is shown to improve the dynamic range by 20–30 dB and the resulting array complexity is shown to be reduced by a factor of 200.