信号子空间
到达方向
算法
子空间拓扑
正交性
协方差矩阵
信号(编程语言)
计算机科学
协方差
噪音(视频)
矩阵的特征分解
测向
数学
天线(收音机)
特征向量
人工智能
电信
统计
几何学
物理
量子力学
图像(数学)
程序设计语言
作者
Chunjing Liu,Xiaoyu Cheng,Jia Su,Yin Yuan
标识
DOI:10.1109/isceic59030.2023.10271196
摘要
Direction of arrival (DOA) estimation is an important research direction in the theory of spatial spectral estimation, and the main DOA algorithms include beam-forming class algorithms and subspace class algorithms, etc. Conventional beam-forming class algorithms have limited estimation accuracy, and subspace class algorithms based on the theory of the eigen decomposition of covariance matrices greatly improve the accuracy of the direction estimation and have a wider applicability. Utilizing the composition structure of the array antenna, the super-resolution algorithm can better process the input signal and improve the parameter estimation ability of the signal in the space of interest. The Root-MUSIC algorithm is based on the eigen decomposition of the covariance matrix of the received signal from the sensor array, and the orthogonality between the separated signal direction vector and the noise subspace is used to determine the DOA polynomials of the Root-MUSIC algorithm, which realizes the signal parameter estimation by solving for the roots on the unit circle. Computer simulations show that the Root-MUSIC algorithm has high accuracy in estimating the DOA of multiple incoherent signals.
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