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作 者:闫锋刚 荣加加 刘帅 沈毅 金铭 YAN Fenggang;RONG Jiajia;LIU Shuai;SHEN Yi;JIN Ming(School of Information and Electrical Engineering, Harbin Institute of Technology (Weihai), Weihai 264209, China;School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China)
机构地区:[1]哈尔滨工业大学(威海)信息与电气工程学院,山东威海264209 [2]哈尔滨工业大学电子与信息工程学院,黑龙江哈尔滨150001
出 处:《系统工程与电子技术》2018年第4期733-738,共6页Systems Engineering and Electronics
基 金:国家自然科学基金(61501142);山东省自然科学基金(ZR2014FQ003);中国博士后科学基金特别资助基金(2015M571414;2016T90289);哈尔滨工业大学(威海)学科建设引导基金(WH20160107)资助课题
摘 要:针对常规子空间类波达方向(direction-of-arrival,DOA)估计中存在的子空间分解计算量过大问题,提出了基于均匀线阵的联合互协方差矩阵(joint cross-covariance matrix,JCCM)DOA估计算法。基于阵列划分和矩阵重构思想,将均匀线阵划分成两个子阵,在求得这两个子阵接收数据互协方差矩阵后,重构一个新的矩阵即JCCM,利用JCCM的部分数据进行线性运算即可得到等价的信号子空间,然后构造多项式并求根,最终实现波达角估计。理论分析和仿真实验证明,算法避开了对协方差矩阵的特征值分解运算,在保证估计精度可接受的同时,有效降低了计算量,取得了更高的估计速度。For the sake of reducing computation complexity caused by the subspace decomposition step in most of the state-of-the-art subspace-based algorithms for direction-of-arrival(DOA)estimation,a joint cross-covariance matrix(JCCM)based algorithm is proposed using a uniform linear array(ULA).Based on the ideas of array division and matrix remodeling,the ULA is divided into two sub-arrays,and two cross-covariance matrices are computed by the received datum of the two sub-arrays,with which a JCCM matrix is further reconstructed.Combing those three matrices,an equivalent signal subspace is found by conducting some low-complexity linear operations,and a polynomial is finally constructed to estimate source DOA without subspace decomposition.Theoretical analysis and simulation results show that the proposed technique can provide acceptable performances with the computational complexity effectively reduced and the faster estimation speed achieved.
关 键 词:阵列信号处理 波达方向估计 子空间分解 联合互协方差矩阵
分 类 号:TN959.2[电子电信—信号与信息处理]
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