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

被引：1
作者：
Jin Y. [1 ]
Hu B.-X. [1 ]
Ji H.-B. [1 ]
机构：
[1] School of Electronic Engineering, Xidian University, Xi'an
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2016年 / 38卷 / 07期
关键词：
L-estimation; Linear frequency modulation (LFM) signal; Optimal L-Cauchy weighted (LCW) method; Parameter estimation; α stable distribution noise;
D O I：
10.3969/j.issn.1001-506X.2016.07.02
中图分类号：
学科分类号：
摘要：
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. © 2016, Editorial Office of Systems Engineering and Electronics. All right reserved.
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页码：1488 / 1495
页数：7
相关论文
共 17 条
  • [1] Zhai Q.L., Zhang J., Fu Q., Study on the technology of LFM pulse compression and appliances in radar system, Modern Electronics Technique, 30, 1, pp. 17-19, (2007)
  • [2] Misaridis T.X., Gammelmark K., Jorgensen C.H., Potential of coded excitation in medical ultrasound imaging, International Ultrasonics Symposium, 38, 3, pp. 183-189, (2000)
  • [3] Mohsen J., Alireza Z., Shideh R., Et al., LFM signal detection and estimation based on sparse representation, Proc. of the IEEE Information Sciences and Systems, pp. 1-5, (2015)
  • [4] Bi G.A., Li X.M., Samson S.C.M., LFM signal detection using LPP-Hough transform, Signal Processing, 91, 6, pp. 1432-1443, (2011)
  • [5] Liu Y.H., Zhou S.Y., Detecting point pattern of multiple line segments using Hough transformation, IEEE Semiconductor Manufacturing, 28, (2015)
  • [6] Song Y., Hu J., Xu J.S., Motion compensation based on keystone transform and Wigner-Hough transform, Applied Mechanics and Materials, 220, pp. 2208-2212, (2012)
  • [7] Yong T., Xing Z.X., Zhong L.L., Time-delay estimation based on fractional lower order statistics, Proc. of the IEEE Wireless Communication and Sensor Network, pp. 50-55, (2014)
  • [8] Erdogan A.Y., Gulum T.O., Durak A.L., Et al., Digital chirp rate adaptation for optimum FMCW interception using Wigner-Hough transform, Proc. of the IEEE Signal Processing and Communications Applications Conference, pp. 1179-1182, (2014)
  • [9] Liu M.Q., Li B.B., Cao C.F., Recognition method of digital modulation signals in non-Gaussian noise, Journal of Electronics & Information Technology, 35, 1, pp. 85-91, (2013)
  • [10] Bin A.A.R., Bin S.A.Z., Bin J.A., Classification of power quality signals using smooth windowed Wigner-Ville distribution, Proc. of the International Conference on Electrical Machines and Systems, pp. 1981-1985, (2010)
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