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A new method combining space-time preprocessing with multistage Wiener filters(STPMWF)is proposed to improve the performance of space-time adaptive processing(STAP)in nonhomogeneous clutter scenario.The new scheme only requires the data from the primary range bin,thus it can suppress discrete interferers efficiently,without calculating the inverse of covariance matrix.Comparing to the original MWF approach,the proposed scheme can be regarded as practical solutions for robust and effective STAP of nonhomogeneous radar data.The theoretical analysis shows that our STPMWF is simple in implementation and fast in convergence.The numeric results by using simulated data exhibit a good agreement with the proposed theory.
A new method combining space-time preprocessing with multistage Wiener filters (STPMWF) is proposed to improve the performance of space-time adaptive processing (STAP) in non-homogeneous clutter scenario. The new scheme only requires the data from the primary range bin, thus it can suppress discrete interferers efficiently, without calculating the inverse of covariance matrix. Comparing to the original MWF approach, the proposed scheme can be regarded as practical solutions for robust and effective STAP of nonhomogeneous radar data. The theoretical analysis shows that our an STPMWF is simple in implementation and fast in convergence. The numeric results by using simulated data exhibit a good agreement with the proposed theory.