摘要
针对信号模型失配情形下的二级嵌套阵列波束形成问题,提出一种基于干扰-噪声协方差矩阵高效重构和半定规划的稳健自适应波束形成算法.该算法首先利用接收信号的对角增长曲线模型,并结合无需空域搜索的ESPRIT方法,精确重构虚拟阵列的干扰-噪声协方差矩阵;其次,利用干扰-噪声协方差矩阵和少量先验信息构造稳健自适应波束形成中的优化问题,有效减小了传统最小方差无失真响应波束形成器在非理想信号环境中的性能损失;最后,采用半定松弛方法得到该优化问题的近似表达形式,即半定规划问题,并借助凸优化工具包求解.仿真结果表明,在不同的输入信噪比和采样快拍数情形下,该算法与现有算法相比,具有更高的输出信干噪比.
For the beamforming problem Jn the two level nested array under the condition of signal model mismateh, this paper proposes a robust adaptive beamforming algorithm based on efficient interferenceplus-noise covariance matrix reconstruction and semi-definite programming（SDP）. Firstly, by using the diagonal growth-curve （DGC） model of the received sigv, al and the search-free ESPRIT method, we reconstruct the interference-plus-noise covariance matrix of the virtual array precisely; then, the interference-plus-noise covariance matrix and a little prior information are applied to construct the optimization problem in robust adaptive beamforming, which can effectively decrease the performance degradation of the traditional MVDR filter in nonideal signal circumstances; finally, the optimization problem can be approximately expressed as an SDP problem by using the SDP relaxation method, and we can resort to the convex optimization software to solve it. Simulation results demonstrate that the proposed method achieves a higher output SINR under different input SNRs or sampling snapshots circumstances as compared to traditional methods.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2015年第6期30-36,共7页
Journal of Xidian University
基金
国家973计划资助项目(2011CB707001)
国家自然科学基金资助项目(61231027,61271292)
关键词
二级嵌套阵列
稳健自适应波束形成
干扰-噪声协方差矩阵重构
半定规划
半定松弛
two level nested array
robust adaptive beamforming
interference-plus-noise covariance matrix reconstruction
semi-definite programming（SDP）
SDP relaxation
