Derivative constrained Gram-Schmidt orthogonalization beamforming method with widened nulls

The performance of the conventional Gram-Schmidt orthogonalization of covariance matrix (RGS) beamforming method will decrease significantly when non-ideal factors exists such as the appearances of fast moving interferences, array platform movement. In order to improve the robustness of interference suppression, a derivative constrained Gram-Schmidt orthogonalization of covariance matrix (CRGS) beamforming method with widened nulls is proposed in this paper. In the proposed method, the number of interference P is initially estimated and the first subspace is reconstructed by Gram-Schmidt orthogonalization of the first P columns of sample covariance matrix. Afterwards, the derivative constrained vectors and the second subspace spanned of these vectors are constructed. At last the adaptive weight vector is obtained by orthogonally projecting the quiescent weight vector onto the interference subspace made up of the first subspace and the second subspace. Based on the numeral simulation results, it is verified that the proposed method can form widened nulls and effectively improve the robustness of interference suppression.