Parameter estimation of 1D GTD scattering center model based on an improved MUSIC algorithm

被引：0

作者：

Zheng S. ^{[1
]}

Zhang X. ^{[2
]}

Guo Y. ^{[2
]}

Zong B. ^{[2
]}

Xu J. ^{[1
]}

机构：

[1] Graduate School, Air Force Engineering University, Xi'an

[2] Air and Missile Defense College, Air Force Engineering University, Xi'an

来源：

Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2020年 / 46卷 / 11期

基金：

中国国家自然科学基金;

关键词：

Conjugate matrix; Multiple Signal Classification (MUSIC) algorithm; One-dimensional Geometric Theory of Diffraction (GTD) scattering center model; Parameter estimation; Scattering center;

D O I：

10.13700/j.bh.1001-5965.2019.0576

中图分类号：

学科分类号：

摘要：

The noise robustness and parameter accuracy are poor when the classical Multiple Signal Classification (MUSIC) algorithm is used to estimate parameters of the one-dimensional Geometric Theory of Diffraction (GTD) scattering center model. To solve this problem, a series of improved MUSIC algorithms are proposed in this paper. Firstly, the improved algorithms construct the conjugate matrixof the original back-scattered data, which utilizes the information of the original data more effectively. Secondly, by averaging the covariance matrix of the original scattering data and its conjugated data, a novel total covariance matrix can be obtained. Finally, quadratic, quartic and other even power are performed on the matrix to obtain another matrix, and thus it can broaden the differences between the eigenvalues of noises and signals, which is equivalent to increasing the signal-to-noise ratio. Simulation results show that the parameter estimation performance and noise robustness are better than those of the classical MUSIC algorithm. © 2020, Editorial Board of JBUAA. All right reserved.

引用

页码：2149 / 2155

页数：6

共 17 条

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