北京航空航天大学学报 ›› 2020, Vol. 46 ›› Issue (11): 2149-2155.doi: 10.13700/j.bh.1001-5965.2019.0576

• 论文 • 上一篇    下一篇

一维GTD散射中心模型参数估计的改进MUSIC算法

郑舒予1, 张小宽2, 郭艺夺2, 宗彬锋2, 徐嘉华1   

  1. 1. 空军工程大学 研究生院, 西安 710051;
    2. 空军工程大学 防空反导学院, 西安 710051
  • 收稿日期:2019-11-11 发布日期:2020-12-01
  • 通讯作者: 张小宽 E-mail:15529037989@163.com
  • 作者简介:郑舒予,男,硕士研究生。主要研究方向:散射中心提取、目标探测与识别;张小宽,男,博士,教授,硕士生导师。主要研究方向:目标探测与识别、雷达目标电磁散射特性研究;郭艺夺,男,博士,讲师。主要研究方向:MIMO雷达信号处理、阵列信号处理;宗彬锋,男,博士,讲师。主要研究方向:天线与电磁波传输;徐嘉华,男,硕士研究生。主要研究方向:目标探测与识别。
  • 基金资助:
    国家自然科学基金(61372033);目标与散射电磁散射辐射重点实验室创新基金(STES2014-2)

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

ZHENG Shuyu1, ZHANG Xiaokuan2, GUO Yiduo2, ZONG Binfeng2, XU Jiahua1   

  1. 1. Graduate School, Air Force Engineering University, Xi'an 710051, China;
    2. Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China
  • Received:2019-11-11 Published:2020-12-01

摘要: 针对利用多重信号分类(MUSIC)算法估计一维几何绕射理论(GTD)的散射中心模型时噪声鲁棒性较差、参数精度不高这一问题,提出一类改进的MUSIC算法。首先,构建原始回波数据的共轭矩阵,有效提高了原始回波数据的利用率;其次,将原始回波数据的协方差矩阵、共轭数据的协方差矩阵叠加取平均,得到一个新的总协方差矩阵;最后,对矩阵作2次方、4次方等偶次方处理,得到另一矩阵,以达到增大信号特征值与噪声特征值之间差距的作用,等效为增大了信噪比。仿真结果表明:所提改进算法的参数估计性能及噪声鲁棒性均要优于经典MUSIC算法。

关键词: 参数估计, 散射中心, 一维几何绕射理论(GTD)散射中心模型, 多重信号分类(MUSIC)算法, 共轭矩阵

Abstract: 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.

Key words: parameter estimation, scattering center, one-dimensional Geometric Theory of Diffraction (GTD) scattering center model, Multiple Signal Classification (MUSIC) algorithm, conjugate matrix

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