摘要
研究均匀圆形阵列的联合二维角度-频率估计问题.基于数据矩阵的重新排列、信号子空间的实数化处理、复数移不变方程以及联合特征值估计,推导出联合估计参数的ESPRIT类算法,该算法将参数估计问题转化为3个具有实特征值的实数矩阵的联合特征值估计问题.通过同时对角化算法估计矩阵的联合特征值,获得了参数联合估计的强可辨识性,即允许信号参数在任何一维任意重复,并可以使估计参数实现自动配对.理论分析和仿真证明了所提算法的有效性.
Investigates the problems of joint 2-D angular and frequency estimation based on uniform circular array （UCA）. Based on the stacking of data matrix, real-processing of signal subspace, complex shift invariance equation and joint eigenvalue estimation, an algorithm is presented to solve this problem and handle the estimation jointly. It is shown that finally this problem turns to the estimation of the real joint eigenvalues of three real matrices and solve the joint eigenvalue estimation by a recently proposed simultaneous diagonalization algorithm. The advantages of the algorithm are attained, i.e. strong identifiability results and autopairing capacity. Thet）retical analysis and simulation prove the effectivity of the algorithm.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2007年第7期630-635,共6页
Transactions of Beijing Institute of Technology
关键词
波达方向
角度-频率估计
均匀圆阵
联合特征值
direction of arrival（DOA）
angular and frequency estimation
uniform circular array
joint eigenvalue
