Generalized Weighted Adaptive Time Delay Estimation Algorithm Based on Minimum Average P Norm

Keni Xu; Wenhong Liu

doi:doi:10.11648/j.jeee.20210905.13

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Generalized Weighted Adaptive Time Delay Estimation Algorithm Based on Minimum Average P Norm

Keni Xu, Wenhong Liu

Published in Journal of Electrical and Electronic Engineering (Volume 9, Issue 5)

Received: 22 September 2021 Accepted: 13 October 2021 Published: 16 October 2021

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Abstract

The time delay estimation algorithm is one of the important factors of sound source localization. The generalized weighted adaptive time delay estimation algorithm is limited by the environmental conditions of signal and noise, and has great limitations in non-Gaussian environments. In order to make the algorithm suitable for non-Gaussian environments, and to retain the advantages of the algorithm in effectively suppressing harmonics, this paper combines the minimum average P norm (LMP) with the generalized weighting function, and proposes a method based on the minimum average P norm. The generalized weighted adaptive time delay estimation algorithm of the number can make the algorithm suitable for non-Gaussian environments, and for the shortcomings of slow iteration speed and large calculation amount for the minimum average P norm, the Sigmoid function is introduced to further improve the parameter selection in the algorithm. MATLAB simulation experiments show that the algorithm in this paper can effectively suppress the existence of harmonics in a non-Gaussian environment, and has strong convergence, high accuracy of time delay estimation, and fast iteration speed. It can be based on time delay estimation in a non-Gaussian environment. The positioning plays a certain role.

Published in	Journal of Electrical and Electronic Engineering (Volume 9, Issue 5)
DOI	10.11648/j.jeee.20210905.13
Page(s)	161-169
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

α Stable Distribution, Generalized Weighting Function, Sigmoid Function, LMP Algorithm

References

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[3]	Carter G C, Nuttall A H, Cable P G The smoothed coherence transform [J]. Proceedings of the IEEE, 1973, 61 (10): 1497-1498.
[4]	Tang Juan, HANG Hongyan. Time Delay Estimation Method Based on Quadratic Correlation [J]. Computer Engineering, 2007 (21): 265-267.
[5]	Xu Xiaosu, Sun Xiaojun, Zhang Tao, Tong Jinwu. Ultra-short baseline underwater acoustic localization algorithm based on repeated generalized cross-correlation time delay estimation [J]. Journal of Chinese Inertial Technology, 2019, 27 (01): 66-71.
[6]	Feintuch, P, Bershad, et al. Time delay estimation using the LMS adaptive filter--Dynamic behavior [J]. Acoustics, Speech and Signal Processing, IEEE Transactions on, 1981, 29 (3): 571-576.
[7]	Wang Hongyu, Qiu Tianshuang. Adaptive noise cancellation and time delay estimation. Dalian: Dalian University of Technology Press, 1999.
[8]	Qin Jingfan, Wei Gang. A variable step size LMS adaptive filtering algorithm based on sigmoid function [J]. Radio Engineering, 1996 (04): 44-47.
[9]	Chen Lei. Simulation analysis of near-field source location algorithm under complex ocean noise environment [D]. Jilin University, 2015.
[10]	Zhou Xingyue, Yang Kunde, A denoising representation framework for underwater acoustic signal recognition, Journal of the Acoustical Society of America, 2020, 147 (4): EL1-EL8.
[11]	Chen Sijia. Research on adaptive filtering algorithm under Alpha stable distributed noise [D]. Hangzhou Dianzi University, 2020.
[12]	Sun Yongmei, Qiu Tianshuang. A new method of HB weighted adaptive time delay estimation under fractional low-order α stable distribution noise [J]. Signal Processing, 2007 (03): 339-342.
[13]	Zhao Ji. Research on adaptive filtering algorithm in Alpha stable distribution environment [D]. University of Electronic Science and Technology of China, 2020.
[14]	Zhao Zhijin, Jin Mingming. The kernel minimum average P-norm algorithm under α stable distributed noise [J]. Application Research of Computers, 2017, 34 (11): 3308-3310+3315.
[15]	Zhang Hongmei, Han Wangang. Research and application of a new variable step size LMS adaptive filtering algorithm [J]. Chinese Journal of Scientific Instrument, 2015, 36 (08): 1822-1830.

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Keni Xu, Wenhong Liu. (2021). Generalized Weighted Adaptive Time Delay Estimation Algorithm Based on Minimum Average P Norm. Journal of Electrical and Electronic Engineering, 9(5), 161-169. https://doi.org/10.11648/j.jeee.20210905.13

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ACS Style

Keni Xu; Wenhong Liu. Generalized Weighted Adaptive Time Delay Estimation Algorithm Based on Minimum Average P Norm. J. Electr. Electron. Eng. 2021, 9(5), 161-169. doi: 10.11648/j.jeee.20210905.13

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AMA Style

Keni Xu, Wenhong Liu. Generalized Weighted Adaptive Time Delay Estimation Algorithm Based on Minimum Average P Norm. J Electr Electron Eng. 2021;9(5):161-169. doi: 10.11648/j.jeee.20210905.13

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@article{10.11648/j.jeee.20210905.13,
  author = {Keni Xu and Wenhong Liu},
  title = {Generalized Weighted Adaptive Time Delay Estimation Algorithm Based on Minimum Average P Norm},
  journal = {Journal of Electrical and Electronic Engineering},
  volume = {9},
  number = {5},
  pages = {161-169},
  doi = {10.11648/j.jeee.20210905.13},
  url = {https://doi.org/10.11648/j.jeee.20210905.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20210905.13},
  abstract = {The time delay estimation algorithm is one of the important factors of sound source localization. The generalized weighted adaptive time delay estimation algorithm is limited by the environmental conditions of signal and noise, and has great limitations in non-Gaussian environments. In order to make the algorithm suitable for non-Gaussian environments, and to retain the advantages of the algorithm in effectively suppressing harmonics, this paper combines the minimum average P norm (LMP) with the generalized weighting function, and proposes a method based on the minimum average P norm. The generalized weighted adaptive time delay estimation algorithm of the number can make the algorithm suitable for non-Gaussian environments, and for the shortcomings of slow iteration speed and large calculation amount for the minimum average P norm, the Sigmoid function is introduced to further improve the parameter selection in the algorithm. MATLAB simulation experiments show that the algorithm in this paper can effectively suppress the existence of harmonics in a non-Gaussian environment, and has strong convergence, high accuracy of time delay estimation, and fast iteration speed. It can be based on time delay estimation in a non-Gaussian environment. The positioning plays a certain role.},
 year = {2021}
}

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TY  - JOUR
T1  - Generalized Weighted Adaptive Time Delay Estimation Algorithm Based on Minimum Average P Norm
AU  - Keni Xu
AU  - Wenhong Liu
Y1  - 2021/10/16
PY  - 2021
N1  - https://doi.org/10.11648/j.jeee.20210905.13
DO  - 10.11648/j.jeee.20210905.13
T2  - Journal of Electrical and Electronic Engineering
JF  - Journal of Electrical and Electronic Engineering
JO  - Journal of Electrical and Electronic Engineering
SP  - 161
EP  - 169
PB  - Science Publishing Group
SN  - 2329-1605
UR  - https://doi.org/10.11648/j.jeee.20210905.13
AB  - The time delay estimation algorithm is one of the important factors of sound source localization. The generalized weighted adaptive time delay estimation algorithm is limited by the environmental conditions of signal and noise, and has great limitations in non-Gaussian environments. In order to make the algorithm suitable for non-Gaussian environments, and to retain the advantages of the algorithm in effectively suppressing harmonics, this paper combines the minimum average P norm (LMP) with the generalized weighting function, and proposes a method based on the minimum average P norm. The generalized weighted adaptive time delay estimation algorithm of the number can make the algorithm suitable for non-Gaussian environments, and for the shortcomings of slow iteration speed and large calculation amount for the minimum average P norm, the Sigmoid function is introduced to further improve the parameter selection in the algorithm. MATLAB simulation experiments show that the algorithm in this paper can effectively suppress the existence of harmonics in a non-Gaussian environment, and has strong convergence, high accuracy of time delay estimation, and fast iteration speed. It can be based on time delay estimation in a non-Gaussian environment. The positioning plays a certain role.
VL  - 9
IS  - 5
ER  -

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Author Information

Keni Xu

School of Electronic Information, Shanghai Dianji University, Shanghai, China
Wenhong Liu

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

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Plain Text BibTeX RIS

APA Style

Keni Xu, Wenhong Liu. (2021). Generalized Weighted Adaptive Time Delay Estimation Algorithm Based on Minimum Average P Norm. Journal of Electrical and Electronic Engineering, 9(5), 161-169. https://doi.org/10.11648/j.jeee.20210905.13

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ACS Style

Keni Xu; Wenhong Liu. Generalized Weighted Adaptive Time Delay Estimation Algorithm Based on Minimum Average P Norm. J. Electr. Electron. Eng. 2021, 9(5), 161-169. doi: 10.11648/j.jeee.20210905.13

Copy | Download

AMA Style

Keni Xu, Wenhong Liu. Generalized Weighted Adaptive Time Delay Estimation Algorithm Based on Minimum Average P Norm. J Electr Electron Eng. 2021;9(5):161-169. doi: 10.11648/j.jeee.20210905.13

Copy | Download

@article{10.11648/j.jeee.20210905.13,
  author = {Keni Xu and Wenhong Liu},
  title = {Generalized Weighted Adaptive Time Delay Estimation Algorithm Based on Minimum Average P Norm},
  journal = {Journal of Electrical and Electronic Engineering},
  volume = {9},
  number = {5},
  pages = {161-169},
  doi = {10.11648/j.jeee.20210905.13},
  url = {https://doi.org/10.11648/j.jeee.20210905.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20210905.13},
  abstract = {The time delay estimation algorithm is one of the important factors of sound source localization. The generalized weighted adaptive time delay estimation algorithm is limited by the environmental conditions of signal and noise, and has great limitations in non-Gaussian environments. In order to make the algorithm suitable for non-Gaussian environments, and to retain the advantages of the algorithm in effectively suppressing harmonics, this paper combines the minimum average P norm (LMP) with the generalized weighting function, and proposes a method based on the minimum average P norm. The generalized weighted adaptive time delay estimation algorithm of the number can make the algorithm suitable for non-Gaussian environments, and for the shortcomings of slow iteration speed and large calculation amount for the minimum average P norm, the Sigmoid function is introduced to further improve the parameter selection in the algorithm. MATLAB simulation experiments show that the algorithm in this paper can effectively suppress the existence of harmonics in a non-Gaussian environment, and has strong convergence, high accuracy of time delay estimation, and fast iteration speed. It can be based on time delay estimation in a non-Gaussian environment. The positioning plays a certain role.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Generalized Weighted Adaptive Time Delay Estimation Algorithm Based on Minimum Average P Norm
AU  - Keni Xu
AU  - Wenhong Liu
Y1  - 2021/10/16
PY  - 2021
N1  - https://doi.org/10.11648/j.jeee.20210905.13
DO  - 10.11648/j.jeee.20210905.13
T2  - Journal of Electrical and Electronic Engineering
JF  - Journal of Electrical and Electronic Engineering
JO  - Journal of Electrical and Electronic Engineering
SP  - 161
EP  - 169
PB  - Science Publishing Group
SN  - 2329-1605
UR  - https://doi.org/10.11648/j.jeee.20210905.13
AB  - The time delay estimation algorithm is one of the important factors of sound source localization. The generalized weighted adaptive time delay estimation algorithm is limited by the environmental conditions of signal and noise, and has great limitations in non-Gaussian environments. In order to make the algorithm suitable for non-Gaussian environments, and to retain the advantages of the algorithm in effectively suppressing harmonics, this paper combines the minimum average P norm (LMP) with the generalized weighting function, and proposes a method based on the minimum average P norm. The generalized weighted adaptive time delay estimation algorithm of the number can make the algorithm suitable for non-Gaussian environments, and for the shortcomings of slow iteration speed and large calculation amount for the minimum average P norm, the Sigmoid function is introduced to further improve the parameter selection in the algorithm. MATLAB simulation experiments show that the algorithm in this paper can effectively suppress the existence of harmonics in a non-Gaussian environment, and has strong convergence, high accuracy of time delay estimation, and fast iteration speed. It can be based on time delay estimation in a non-Gaussian environment. The positioning plays a certain role.
VL  - 9
IS  - 5
ER  -

Copy | Download