In order to solve the problem in Automatic Identification System (AIS) that the signal in the target slot cannot be correctly received due to partial overlap of signals in adjacent time slots, the paper introduces a new criterion: maximum expected signal power (MESP) and proposes a novel beamforming algorithm based on generalized singular value decomposition (GSVD) and orthogonal projection. The algorithm employs GSVD to estimate the signal subspace, and adopts orthogonal projection to project the received signal onto the orthogonal subspace of the non-target signal. Then, beamforming technique is used to maximize the output power of the target signal on the basis of MESP. Theoretical analysis and simulation results show the effectiveness of the proposed algorithm.

Blind beamforming plays an important role in multiple-input multiple-output (MIMO) Systems, radar, cognitive radio, and system identification. In this paper, we propose a new algorithm for multiple blind beamforming algorithm based on the least square constant modulus algorithm (LSCMA). The new method consists of the following three parts: (a) beamforming of one signal with LSCMA. (b) direction-of-arrival (DOA) estimation of the remaining signals by rooting the weight vector polynomial. (c) beamforming of the remaining signals with linear constraints minimum variance (LCMV) method. After the convergence of LSCMA, one signal is captured and the arrival angles of the remaining signals can be obtained by rooting the weight vector polynomial. Therefore, beamforming can be quickly established for the remaining signals using LCMV method. Simultaneously the DOA of the signals can also be obtained. Simulation results show the performance of the presented method.