一种联合修正的稳健Capon波束形成算法

Robust Capon Beamforming Algorithm Based on Joint Estimation Covariance and Steering Vector

指出了水平定向天线阵波束形成的主要难点,没有固定相位中心和受交叉极化来波的影响。阵列受随机性误差使得导向矢量存在较大失配,从而导致传统Capon算法性能下降甚至失效。在阵列误差模型下,给出了基于协方差矩阵与导向矢量联合修正的稳健Capon波束形成算法。该算法首先基于收缩得到一个增强的协方差矩阵,然后通过最大化Capon输出功率实现对导向矢量的修正,同时增加二次型约束防止修正的导向矢量接近于干扰导向矢量上。该算法可转化为二次约束二阶规划问题,并通过凸优化进行求解。仿真结果表明,该算法对天线阵模型中误差矩阵具有一定的稳健性,且较其他稳健算法具有较好的性能。

The main difficulties of the directional antenna array beamforming are pointed out, that is, there is no fixed phase center and there is influence of cross-polarized wave. The random error causes a large steering vector mismatch, resulting in the traditional Capon algorithm performance degradation or even invalidity. A robust Capon beamforming algorithm based on joint estimation covariance and steering vector is proposed under the array error model. It obtains an enhanced covariance matrix based on the shrinkage meth- od firstly, and then achieves steering vector by maximizing the Capon output power, while adding a quadratic constraint to prevent the modified steering vector from closing to the interference. The algorithm can be transformed into the quadratically constrainted quadratic programming（QCQP） problem, which can be solved by convex optimization. Simulation results show that the algorithm has certain robustness for antenna array model error, and has better performance compared with other robust algorithms.