In general, space–time adaptive processing (STAP) can achieve excellent clutter suppression and moving target detection performance in the airborne multiple-input multiple-output (MIMO) radar for the increasing system degrees of freedom. However, the performance improvement is accompanied by the dramatic increase in computational cost and training sample demanding. Though reduced-dimensional STAP can alleviate these problems, its performance will still be heavily degraded for insufficient training sample support, which will frequently be met in the airborne MIMO radar. Hence, in this work, by utilizing the special structure of the MIMO radar signal, the STAP filter coefficients of the conventional joint domain localized processing method are constrained as the Kronecker product form so that the computational cost and training sample demanding are further reduced. Then, the tri-iterative algorithm is applied to find the desired solution. Simulation results demonstrate the effectiveness of the proposed method.
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This work was sponsored in part by National Natural Science Foundation of China under Grants 61503300, 41601353 and 61801383; the Scientific Research Plan of Education Department of Shaanxi Province under Grant 17JK0789.
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