摘要
基于最大非圆率非圆信号特点,提出一种实值张量旋转不变子空间(estimation signal parameters via rotational invariance techniques,ESPRIT)算法。首先,通过研究张量与矩阵之间的转化关系,将阵列接收数据矩阵推广到张量空间;然后,利用欧拉公式将阵列接收数据张量转化成余弦与正弦数据张量,根据阵列维数将其分别在各维上加以拼接,并对拼接的实值数据张量做高阶奇异值分解,获取信号子空间;最后,通过构造选择矩阵和进行特征分解,来联合估计阵列各维相位差,实现波达方向估计。实验仿真结果表明,此算法具有良好的分辨力和测角精度。
Based on the characteristics of non-circular signals of the maximum non-circular rate？ a real-valuetensor estimation signal parameters via rotational invariance techniques （ESPRIT ） algorithm is put forward.F irstly, the array receiving data matrix is extended to tensor space by studying the relationship between tensorand matrix. Then, the array receiving data tensor is turned into cosine and sine data tensor by using the Eulerformula, according to the array dimensions to concatenate cosine and sine data tensor in each dimension, respectively, and obtain the signal subspace through a higher-order singular value decomposition of real-value concatenationtensor data. Finally？ phase difference is estimated jointly in each dimension to realize direction of arrival（DOA） estimation by constructing the selection matrix and eigen decomposition. The experimental simulationresults show that this algorithm has a better resolution and angle measurement accuracy.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2016年第9期1975-1980,共6页
Systems Engineering and Electronics
基金
航空科学基金(201401P6001)
中央高校基本科研业务费专项资金(HEUCF150804)资助课题
关键词
波达方向估计
非圆信号
高阶奇异值分解
张量
旋转不变子空间算法
direction of arrival （DOA） estimation
non-circular signals
higher-order singular value decomposition
tensor
estimation signal parameters via rotational invariance techniques （ESPRIT ） algorithm
