A robust adaptive array based on signal subspace approach

In this note, we propose a signal subspace approach that improves the performance of a beam steered adaptive array in the presence of steering errors due to look-direction error (LDE) and/or random steering error (RSE). In the method, the degrees of freedom (DOF) are reduced so as not to cancel the desired signal while preserving the optimal characteristic of the array, and thus the weights of the array are determined by a linear combination of the eigenvectors of the signal subspace. The proposed method works as far as the eigen decomposition of the input covariance matrix into signal and noise subspaces is possible. The proposed method improves noticeably the array performance of the beam steered array in the presence of steering errors and provides the optimum array performance in the absence of steering errors