Adaptive beamforming based on nonuniform linear arrays with enhanced degrees of freedom

In traditional adaptive beamforming, the number of degrees of freedom is limited by the number of sensors in the array. In this paper, a new adaptive beamforming scheme is developed based on the nonuniform linear array structure, whose degrees of freedom can be much greater than the number of physical sensors in the array. In the proposed method, the original covariance matrix of the received array data is first processed to obtain a new matrix which has a larger size. Then this augmented covariance matrix is used to calculate the optimum weight vector of the beamformer. Based on the two level nested array, the proposed beamformer can provide O(N2) degrees of freedom by using only O(N) sensors. It can be used to reduce the implementation complexity of a large sensor array, where only a small number of sensors are selected to calculate the equivalent optimal weight coefficients for the original full array. Simulation results are provided to verify the performance improvement of the proposed beamformer.