|Table of Contents|

Parameter estimation for clutter Weibull-distributed model based on improved MLE-NR method

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2014年06期
Page:
720-
Research Field:
Publishing date:

Info

Title:
Parameter estimation for clutter Weibull-distributed model based on improved MLE-NR method
Author(s):
Hou ZhiCui CanZhang DuoWu Wen
Ministerial Key Laboratory of JGMT,NUST,Nanjing 210094,China
Keywords:
maximum likelihood estimation-Newton Raphson method Weibull-distributed model parameter estimation initial value Hessian matrix Monte-Carlo simulation
PACS:
N945.12
DOI:
-
Abstract:
To solve the problem of the traditional maximum likelihood estimation-Newton Raphson(MLE-NR)method that the initial value must be selected carefully to ensure the convergence of iteration,an improved MLE-NR method for parameter estimation of clutter Weibull-distributed model is presented here.The Hessian matrix of the iteration point is calculated,the divergent points in iteration process and wrong initial iteration points are adjusted to a convergence region according to the determinant value of the Hessian matrix,so that the divergent iteration is convergent again and the model parameter can be estimated correctly.Monte-Carlo simulations are proceeded with N=500 and the lengths of the random sample data are 256,512,1 024,2 048,4 096 respectively.The results show that the improved MLE-NR method is convergent for sample data with different length.The Monte-Carlo simulation and processing results based on measured data demonstrate the effectiveness and robustness of this method.

References:

[1] Shnidman D A.Radar detection in clutter[J].IEEE Transactions on Aerospace and Electronic Systems,2005,41(3):1056-1067.
[2]Shnidman D A.Generalized radar clutter model[J].IEEE Transactions on Aerospace and Electronic Systems,1999,35(3):857-865.
[3]Kaio N,Osaki S.Comparisons of point estimation methods in the 2-parameter Weibull distribution[J].IEEE Transactions on Reliability,1980,R-29(1):21.
[4]Cran G W.Moment estimators for the 3-parameter Weibull distribution[J].IEEE Transactions on Reliability,1988,37(4):360-363.
[5]Tuzuner A,Yu Zuwei.A theoretical analysis on parameter estimation for the Weibull wind speed distribution[A].2008 IEEE Power and Energy Society General Meeting-conversion and Delivery of Electrical Energy in the 21st Century[C].Pittsburgh,PA,USA:IEEE,2008:1-6.
[6]Cohen A C.Maximum likelihood estimation in the Weibull distribution based on complete and on censored samples[J].Technometrics,1965,7(4):579-588.
[7]Steven M K.Fundamentals of statistical signal processing:Estimation theory[M].New Jersey,USA:Prentice Hall PTR,1993.
[8]杨万海.雷达系统建模与仿真[M].西安:西安电子科技大学出版社,2007.
[9]Aldrich J R A.Fisher and the making of maximum likelihood 1912-1922[J].Statistical Science,1997,12(3):162-176.
[10]Abatzoglou T J.Fast maximum likelihood joint estimation of frequency and frequency rate[A].IEEE International Conference of Acoustic,Speech and Signal Processing(ICASSP'86)[C].Tokyo, Japan:IEEE,1986:1409-1412.
[11]胥嘉佳,刘渝,邓振淼.LFM信号参数估计的牛顿迭代方法初始值研究[J].电子学报,2009,37(3):598-602. Xu Jiajia,Liu Yu,Deng Zhenmiao.The starting point problem of parameters estimation for LFM signal based on Newton's method[J].Acta Electronica Sinica,2009,37(3):598-602.
[12]蔡大用,白峰杉.高等数值分析[M].北京:清华大学出版社,1997.
[13]卢卫君,方丽菁.Hessian矩阵的若干应用[J].桂林工学院学报,2007,27(3):455-459. Lu Weijun,Fang Lijing.Applications of Hessian matrix[J].Journal of Guilin University of Technology,2007,27(3):455-459.
[14]侯志,缪晨,张金栋,等.复杂探测背景下的LFMCW雷达动目标二维检测方法[J].西安电子科技大学学报(自然科学版),2011,38(4):167-172. Hou Zhi,Miao Chen,Zhang Jindong,et al.Moving target detection and processing method of LFMCW radar under complex background[J].Journal of Xidian University(Natural Science),2011,38(4):167-172.
[15]Zhang J,Wu W,Fang D G.360°scanning multi-beam antenna based on homogeneous ellipsoidal lens fed by circular array[J].Electronics Letters,2011,47(5):298-300.

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Last Update: 2014-12-31