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Robust Detection Method of Arrival Time Difference Under Minimum Maximum Entropy Criterion

Received: 6 February 2017    Accepted: 24 March 2017    Published: 10 April 2017
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Abstract

Accurate measurement of arrival time difference is one of the key technologies in many areas, such as the global positioning system. Due to the effects of environmental noises around receiver, the classic methods under least mean-square error rule are the lack of robustness. In this paper, a robust method of the time difference detection is addressed based on the minimum maximum entropy, referred to MMEATD. The maximum entropy function used in this method is a smooth approximation of the L1 norm. It has robustness to large outliers, but also is differentiable. Under the minimum maximum entropy criterion, the adaptive filter weight vector will be convergence, and its peak position indicates the arrival time difference. The computer simulation experiments show the estimation performance of this algorithm under different signal and noise ratio or different impulsive noise intension. Meanwhile, its estimation performance is compared with minimum mean square error algorithm. Results show that the proposed method has a good robustness under the impulsive noise environment.

Published in Journal of Electrical and Electronic Engineering (Volume 5, Issue 2)
DOI 10.11648/j.jeee.20170502.16
Page(s) 63-67
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Time Difference Detection, Impulsive Noises, Robustness, Minimum Maximum Entropy, Adaptive Filter

References
[1] Lin Zhao, Jicheng Ding, Xuefei Ma. The principle and application of satellite navigation. Northwestern Polytechnical University Press, 2011.
[2] Wenhong Liu. Under the impulse noise time delay estimation method and application research. Ph.D. Dissertation, Dalian University of Technology, 2007.
[3] Xinyu Ma. Robust signal processing in impulsive noise with stable distributions: estimation, identification and equalization. Ph.D. Dissertation, University of Southern California, 1996.
[4] Chrysostomos Loizos Nikias, Shao Ming. Signal processing with Alpha-stable distributions. New York: John Wiley & Sons Inc, 1995.
[5] Qiu Tianshuang Wang Hong, Zhang Yang, et al. The Non-linear transform based robust adaptive latency change estimation of evoked potentials. Methods of Information in Medicine, 2002, 41 (4): 331-336.
[6] Wang Zhishun, He Zhenya, Chen Jiande. Robust time delay estimation of bioelectric signals using absolute deviation neural network. IEEE Trans. On Biomedical Engineering, 2005, 52 (3): 454-462.
[7] Xingsi Li. An effective solution to non-linear minimax problem. Chinese Science Bulletin, 1991, 36 (9): 1448-1450.
[8] Xingsi Li. Effective solution of a class of non-differentiable optimization problems. China Science (A), 1994, 24 (4): 371-377.
[9] Huanwen Tang, Zhang Li. Maximum entropy method for convex programming. Chinese science bulletin, 1994, 39 (8): 682-684.
[10] Chao Tang, Dexin Cao, Yanjiang Wu. Linear L1 minimization problem of the entropy function continuation method. Journal of Applied Mathematics and Computational Mathematics, 2006, 20 (1): 99-102.
[11] Wenhong Liu, Yuanyuan Wang, Bin Wang. The minimum maximum entropy under impulse noise adaptive time delay estimation. Journal of instruments and meters, 2008, 29 supplement IV (4): 519-522.
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Cite This Article
  • APA Style

    Wenhong Liu, Junhao Li, Niansheng Chen, Guangyu Fan. (2017). Robust Detection Method of Arrival Time Difference Under Minimum Maximum Entropy Criterion. Journal of Electrical and Electronic Engineering, 5(2), 63-67. https://doi.org/10.11648/j.jeee.20170502.16

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    ACS Style

    Wenhong Liu; Junhao Li; Niansheng Chen; Guangyu Fan. Robust Detection Method of Arrival Time Difference Under Minimum Maximum Entropy Criterion. J. Electr. Electron. Eng. 2017, 5(2), 63-67. doi: 10.11648/j.jeee.20170502.16

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    AMA Style

    Wenhong Liu, Junhao Li, Niansheng Chen, Guangyu Fan. Robust Detection Method of Arrival Time Difference Under Minimum Maximum Entropy Criterion. J Electr Electron Eng. 2017;5(2):63-67. doi: 10.11648/j.jeee.20170502.16

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  • @article{10.11648/j.jeee.20170502.16,
      author = {Wenhong Liu and Junhao Li and Niansheng Chen and Guangyu Fan},
      title = {Robust Detection Method of Arrival Time Difference Under Minimum Maximum Entropy Criterion},
      journal = {Journal of Electrical and Electronic Engineering},
      volume = {5},
      number = {2},
      pages = {63-67},
      doi = {10.11648/j.jeee.20170502.16},
      url = {https://doi.org/10.11648/j.jeee.20170502.16},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20170502.16},
      abstract = {Accurate measurement of arrival time difference is one of the key technologies in many areas, such as the global positioning system. Due to the effects of environmental noises around receiver, the classic methods under least mean-square error rule are the lack of robustness. In this paper, a robust method of the time difference detection is addressed based on the minimum maximum entropy, referred to MMEATD. The maximum entropy function used in this method is a smooth approximation of the L1 norm. It has robustness to large outliers, but also is differentiable. Under the minimum maximum entropy criterion, the adaptive filter weight vector will be convergence, and its peak position indicates the arrival time difference. The computer simulation experiments show the estimation performance of this algorithm under different signal and noise ratio or different impulsive noise intension. Meanwhile, its estimation performance is compared with minimum mean square error algorithm. Results show that the proposed method has a good robustness under the impulsive noise environment.},
     year = {2017}
    }
    

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  • TY  - JOUR
    T1  - Robust Detection Method of Arrival Time Difference Under Minimum Maximum Entropy Criterion
    AU  - Wenhong Liu
    AU  - Junhao Li
    AU  - Niansheng Chen
    AU  - Guangyu Fan
    Y1  - 2017/04/10
    PY  - 2017
    N1  - https://doi.org/10.11648/j.jeee.20170502.16
    DO  - 10.11648/j.jeee.20170502.16
    T2  - Journal of Electrical and Electronic Engineering
    JF  - Journal of Electrical and Electronic Engineering
    JO  - Journal of Electrical and Electronic Engineering
    SP  - 63
    EP  - 67
    PB  - Science Publishing Group
    SN  - 2329-1605
    UR  - https://doi.org/10.11648/j.jeee.20170502.16
    AB  - Accurate measurement of arrival time difference is one of the key technologies in many areas, such as the global positioning system. Due to the effects of environmental noises around receiver, the classic methods under least mean-square error rule are the lack of robustness. In this paper, a robust method of the time difference detection is addressed based on the minimum maximum entropy, referred to MMEATD. The maximum entropy function used in this method is a smooth approximation of the L1 norm. It has robustness to large outliers, but also is differentiable. Under the minimum maximum entropy criterion, the adaptive filter weight vector will be convergence, and its peak position indicates the arrival time difference. The computer simulation experiments show the estimation performance of this algorithm under different signal and noise ratio or different impulsive noise intension. Meanwhile, its estimation performance is compared with minimum mean square error algorithm. Results show that the proposed method has a good robustness under the impulsive noise environment.
    VL  - 5
    IS  - 2
    ER  - 

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Author Information
  • School of Electronic and Information, Shanghai Dianji University, Shanghai, China

  • School of Electrical Engineering, Shanghai Dianji University, Shanghai, China

  • School of Electronic and Information, Shanghai Dianji University, Shanghai, China

  • School of Electronic and Information, Shanghai Dianji University, Shanghai, China

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