采用序列二次规划求解的稳健波束形成新算法  

Novel robust beamforming algorithm using sequential quadratic programming

作　　者：虞泓波 冯大政[1] 解虎[1] 

机构地区：[1]西安电子科技大学雷达信号处理国家重点实验室,陕西西安710071

出　　处：《西安电子科技大学学报》2016年第2期41-45,204,共6页Journal of Xidian University

基　　金：国家自然科学基金资助项目(61271293)

摘　　要：利用尽可能少的先验信息进行导向矢量估计的稳健波束形成方法利用半正定松弛算法求解,面临可能存在性能损失、计算复杂度高的问题,针对该问题提出一种采用序列二次规划求解的新算法.首先利用一阶泰勒级数将原始模型线性近似为凸优化问题,然后对该子凸优化问题进行迭代求解.此外,还考虑了协方差矩阵失配问题,提出最坏情况性能最优的序列二次规划算法提高序列二次规划算法的性能.理论分析和仿真实验表明,序列二次规划算法收敛速度较快,收敛点逼近原始问题最优解,与现有半正定松弛算法相比,能够有效降低计算量,该算法在小参数值时即可有效改进序列二次规划算法的性能.Aiming at the probably existing performance loss and high computational complexity of the robust beamforming based on steering vector estimation with as little prior information as possible which is solved by the semi-definite relaxation（SDR）approach,a novel robust beamforming algorithm using sequential quadratic programming（SQP）is proposed.The original non-convex problem is linearly approximated to a convex subproblem using the first order Taylor＇s series,and the optimal solution is found out by solving the convex subproblem iteratively.Moreover,considering the mismatch of the sample covariance matrix,the SQP-WC method based on worst-case performance optimization is presented to improve the performance of the proposed SQP method.Theoretical analysis and simulation results show that the proposed SQP algorithm can converge fast and its convergence point approximates the optimal solution to the original problem, which indicates that the SQP method can effectively reduce the computational complexity compared with the SDR method,and furthermore,the SQP-WC method can effectively improve the performance of the SQP method with a small parameter.

关 键 词：导向矢量估计 稳健波束形成 序列二次规划 线性近似 最坏情况性能最优 

分 类 号：TN958.92[电子电信—信号与信息处理]