Design of partially adaptive array beamformers based on information theoretic criteria

In this paper, two basic problems in designing partially adaptive array beamformers based on the structure of generalized sidelobe canceller (GSC) are considered. The first problem is to decide the proper dimension of the required adaptive weight vector. Using the information of the array output power, we develop the detection formulas for the information theoretic criteria AIC and MDL to decide the proper dimension of the adaptive weight vector. If the input noise power is unknown a priori, efficient methods are proposed for estimating the input noise power in both cases, with and without the desired signal, to make the detection formulas still feasible. The second problem is to find the most appropriate channel signals for weight adaptation for efficiently canceling interference. An efficient method based on the maximum power reduction criterion is presented for selecting the most desired channel signals from the output of the signal blocking matrix. Theoretical analysis concerning the performance of the proposed methods is made. Computer simulations showing the effectiveness of the proposed methods are also provided