系统工程与电子技术

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α稳定分布噪声下基于最优L-柯西加权的LFM信号参数估计

金艳, 胡碧昕, 姬红兵   

  1. 西安电子科技大学电子工程学院, 陕西 西安 710071
  • 出版日期:2016-06-24 发布日期:2010-01-03

Parameter estimation of LFM signals based on optimal L-Cauchy weighted method in α stable distribution noise

JIN Yan, HU Bi-xin, JI Hong-bing   

  1. School of Electronic Engineering, Xidian University, Xi’an 710071, China
  • Online:2016-06-24 Published:2010-01-03

摘要:

针对传统维格纳霍夫变换(Wigner-Ville Hough transform, WHT) 时频分析方法在稳定分布噪声环境下性能退化的问题,基于L-估计理论,提出了可有效抑制该噪声的最优L柯西加权(L-Cauchy weighted, LCW)新方法。3En准则是一种常用的异常值剔除方法,其可从数理统计的角度对异常值进行有效抑制,对此,结合柯西分布提出了基于分散系数的异常值剔除准则,并依据数值仿真选取降噪效果最优的分散系数γ。在LCW方法有效抑制α稳定分布噪声的基础上,采用WHT对线性调频(linear frequency modulation, LFM)信号进行参数估计。仿真结果表明,最优γ值的选取与该文提出的异常值剔除准则一致,且与基于分数低阶、加权Myriad滤波以及L-估计等多种方法相比,提出的基于LCW的WHT(LCW-WHT,LW)方法在强脉冲噪声下具有良好的鲁棒性和优良的LFM信号参数估计性能。

Abstract:

To address the problem that the traditional timefrequency analysis methods based on the Wigner Hough transform (WHT) degrade severely in stable noise environment, an optimal L-Cauchy weighted (LCW) method based on the L-estimation theory which can effectively suppress this kind of noise is proposed. The 3En criterion is a kind of commonly used method to eliminate outliers, which can effectively restrain the outliers from the point of mathematical statistics. Combined with the Cauchy distribution, a method to restrain outliers based on the dispersion coefficient is proposed, and the optimal parameter value of α in the LCW method could be selected by numerical simulation. The parameters of noisy linear frequency modulation (LFM) signals can be estimated by the WHT method based on the LCW method. Simulation results show that the optimal parameter value of α consists with the proposed method for restraining outliers. Compared with the L-estimation, the fractional lower order statistics as well as the weighted Myriad filter based time frequency analysis methods, the proposed method has better performance for the LFM signal parameter estimation and it is robust to the α stable distribution noise.