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针对标准Capon波束形成器在存在导向矢量失配时性能急剧下降问题,提出了一种基于半定规划和秩-1分解的稳健波束形成算法.该方法通过对实际导向矢量的估计提高自适应波束形成算法稳健性.首先分别从干扰抑制和噪声抑制两个方面推导了新导向矢量应满足的约束条件,并证明了利用矩阵滤波器构造约束条件的合理性;构造了估计最优导向矢量的优化问题并将其转化为易于求解的松弛半定规划问题,同时引入秩-1分解理论用于优化问题的求解.仿真分析表明,与目前较为常见的算法相比,本文算法只需利用期望信号可能入射区间这一先验信息,能获得更高输出信干噪比和功率估计精度.
A robust beamforming algorithm based on semidefinite programming and rank-1 decomposition is proposed for the standard Capon beamformer in the presence of steep drop of steering vector mismatch. This method improves adaptive beamforming by estimating the actual steering vector Form the robustness of the algorithm.Firstly, the constraints that the new steering vectors should satisfy are deduced respectively from the two aspects of interference suppression and noise suppression, and the rationality of using the matrix filter to construct the constraints is proved. The optimization of estimating the optimal steering vectors Problem and convert it into an easy-to-solve loosely-semidefinite programming problem, and introduce the rank-1 decomposition theory to solve the optimization problem.The simulation results show that compared with the most common algorithms, the proposed algorithm only uses the expected signal The a priori information of the incident interval can obtain the higher output SINR and the power estimation accuracy.