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.

Highlights

  • Methodology ArticleRobust Detection Method of Arrival Time Difference Under Minimum Maximum Entropy Criterion

  • In many areas, such as the global positioning system, arrival time difference detection accurately is one of the core technologies [1]

  • When noises are in conformity with the Gaussian distribution, traditional methods under minimum mean square error criterion have good estimation performance, and have advantageous for the theoretical analysis

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Summary

Methodology Article

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

Introduction
Maximum Entropy Function
Time Difference Detection Under Minimum Maximum Entropy Criterion
Computer Simulations
Conclusions
Full Text
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