Robust Detection Method of Arrival Time Difference Under Minimum Maximum Entropy Criterion
Journal of Electrical and Electronic Engineering
Volume 5, Issue 2, April 2017, Pages: 63-67
Received: Feb. 6, 2017; Accepted: Mar. 24, 2017; Published: Apr. 10, 2017
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Wenhong Liu, School of Electronic and Information, Shanghai Dianji University, Shanghai, China
Junhao Li, School of Electrical Engineering, Shanghai Dianji University, Shanghai, China
Niansheng Chen, School of Electronic and Information, Shanghai Dianji University, Shanghai, China
Guangyu Fan, School of Electronic and Information, Shanghai Dianji University, Shanghai, China
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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.
Time Difference Detection, Impulsive Noises, Robustness, Minimum Maximum Entropy, Adaptive Filter
To cite this article
Wenhong Liu, Junhao Li, Niansheng Chen, Guangyu Fan, Robust Detection Method of Arrival Time Difference Under Minimum Maximum Entropy Criterion, Journal of Electrical and Electronic Engineering. Vol. 5, No. 2, 2017, pp. 63-67. doi: 10.11648/j.jeee.20170502.16
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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