A method of performing space based Ground Moving Target Indication (GMTI) using radar interferometric processing is presented. The algorithm, referred to as Scanned Pattern Interferometric Radar (SPIR), uses the high angular variability of a sparse array Point Spread Function (PSF) to collect sufficient data from the signal return that the clutter and targets can be separated without an a priori assumption of the clutter statistics. It is shown that clutter within the main lobe of the individual aperture pattern can indeed be separated from the targets, using the deterministic geometric relationship between observation direction and clutter Doppler shift. If the computational domain is extended to the side lobes of the gain pattern, clutter entering through these lobes can also be extracted. Constraints on the cluster geometry are derived from the invertibility of the PSF matrix.
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