Minimum Norm Constraint Based MVDR Beamforming Algorithm
Aiming at the difficulty in effectively balancing and optimizing interference and noise suppression sim-ultaneously of the traditional minimum variance distortionless response(MVDR)beamforming algorithm,an improved MVDR beamforming algorithm based on biorthogonal decomposition was proposed in this paper.By eigen-decomposition of the autocorrelation array of the array received signal,the large eigenvalue was subtracted from the noise power and the corresponding eigenvector of the large eigenvalue,and the biorthogonal base of the array manifold matrix vector is constructed to replace the inverse form of the autocorrelation array in the MVDR algorithm to form the weighting coefficient.The noise power was estimated by the average of small eigenvalues.The obtained weight coefficients correspond to the minimum norm solution under the linear constraint.Simula-tion analysis showed that the algorithm could effectively form nulls at the interference locations,which was ben-eficial for subsequent noise filtering in the time dimension and had better interfere and noise suppression per-formance than MVDR algorithm.
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