The On-Chip D-LMS Filter Design Method of Wireless Sensor Node Based on FPGA

In the real-time position technology of underground shallow source, the signal denoising performance of wireless sensor nodes directly determines the location speed and accuracy of underground burst point. Because of the complexity and randomness of the underground medium and the fact that undergrou...

Full description

Saved in:
Bibliographic Details
Main Authors: Jian Li, Maojin Li, Ming Meng, Zepeng Liu
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Shock and Vibration
Online Access:http://dx.doi.org/10.1155/2020/4850438
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849467786645995520
author Jian Li
Maojin Li
Ming Meng
Zepeng Liu
author_facet Jian Li
Maojin Li
Ming Meng
Zepeng Liu
author_sort Jian Li
collection DOAJ
description In the real-time position technology of underground shallow source, the signal denoising performance of wireless sensor nodes directly determines the location speed and accuracy of underground burst point. Because of the complexity and randomness of the underground medium and the fact that underground explosion is a nonstationary transient process, the problems of low convergence rate and poor steady-state performance of the filter exist when the existing LMS algorithm is used for signal denoising. In light of the above concerns, this paper comes up with a signal denoising algorithm and hardware implementation method based on D-LMS (delay-LMS). Firstly, according to the autocorrelation function characteristic of random signal, using the principle that the autocorrelation function time delay characteristic of narrowband signal such as explosion vibration signal is better than that of wideband random signal such as ground noise, the D-LMS filter algorithm is constructed by introducing the time delay parameter. Secondly, the selection method of key parameters in D-LMS hardware implementation is analyzed. Thirdly, the corresponding hardware circuit is designed by FPGA, and the simulation is carried out. Numerical simulation and experimental verification show that compared with the existing LMS improved algorithm, the D-LMS algorithm proposed in this paper has higher denoising stability and better denoising effect. Compared with the signal postprocessing method based on the host computer, the signal denoising speed of this method is significantly improved. This method will provide a powerful theoretical method to solve the problem of high-precision and fast source positioning and provide technical support for the development of high-speed and real-time source positioning instruments.
format Article
id doaj-art-e65cc7654b1f42e087f801c1f805b0aa
institution Kabale University
issn 1070-9622
1875-9203
language English
publishDate 2020-01-01
publisher Wiley
record_format Article
series Shock and Vibration
spelling doaj-art-e65cc7654b1f42e087f801c1f805b0aa2025-08-20T03:26:04ZengWileyShock and Vibration1070-96221875-92032020-01-01202010.1155/2020/48504384850438The On-Chip D-LMS Filter Design Method of Wireless Sensor Node Based on FPGAJian Li0Maojin Li1Ming Meng2Zepeng Liu3Shanxi Key Laboratory of Information Detection and Processing, North University of China, Taiyuan 030051, ChinaShanxi Key Laboratory of Information Detection and Processing, North University of China, Taiyuan 030051, ChinaShanxi Key Laboratory of Information Detection and Processing, North University of China, Taiyuan 030051, ChinaShanxi Key Laboratory of Information Detection and Processing, North University of China, Taiyuan 030051, ChinaIn the real-time position technology of underground shallow source, the signal denoising performance of wireless sensor nodes directly determines the location speed and accuracy of underground burst point. Because of the complexity and randomness of the underground medium and the fact that underground explosion is a nonstationary transient process, the problems of low convergence rate and poor steady-state performance of the filter exist when the existing LMS algorithm is used for signal denoising. In light of the above concerns, this paper comes up with a signal denoising algorithm and hardware implementation method based on D-LMS (delay-LMS). Firstly, according to the autocorrelation function characteristic of random signal, using the principle that the autocorrelation function time delay characteristic of narrowband signal such as explosion vibration signal is better than that of wideband random signal such as ground noise, the D-LMS filter algorithm is constructed by introducing the time delay parameter. Secondly, the selection method of key parameters in D-LMS hardware implementation is analyzed. Thirdly, the corresponding hardware circuit is designed by FPGA, and the simulation is carried out. Numerical simulation and experimental verification show that compared with the existing LMS improved algorithm, the D-LMS algorithm proposed in this paper has higher denoising stability and better denoising effect. Compared with the signal postprocessing method based on the host computer, the signal denoising speed of this method is significantly improved. This method will provide a powerful theoretical method to solve the problem of high-precision and fast source positioning and provide technical support for the development of high-speed and real-time source positioning instruments.http://dx.doi.org/10.1155/2020/4850438
spellingShingle Jian Li
Maojin Li
Ming Meng
Zepeng Liu
The On-Chip D-LMS Filter Design Method of Wireless Sensor Node Based on FPGA
Shock and Vibration
title The On-Chip D-LMS Filter Design Method of Wireless Sensor Node Based on FPGA
title_full The On-Chip D-LMS Filter Design Method of Wireless Sensor Node Based on FPGA
title_fullStr The On-Chip D-LMS Filter Design Method of Wireless Sensor Node Based on FPGA
title_full_unstemmed The On-Chip D-LMS Filter Design Method of Wireless Sensor Node Based on FPGA
title_short The On-Chip D-LMS Filter Design Method of Wireless Sensor Node Based on FPGA
title_sort on chip d lms filter design method of wireless sensor node based on fpga
url http://dx.doi.org/10.1155/2020/4850438
work_keys_str_mv AT jianli theonchipdlmsfilterdesignmethodofwirelesssensornodebasedonfpga
AT maojinli theonchipdlmsfilterdesignmethodofwirelesssensornodebasedonfpga
AT mingmeng theonchipdlmsfilterdesignmethodofwirelesssensornodebasedonfpga
AT zepengliu theonchipdlmsfilterdesignmethodofwirelesssensornodebasedonfpga
AT jianli onchipdlmsfilterdesignmethodofwirelesssensornodebasedonfpga
AT maojinli onchipdlmsfilterdesignmethodofwirelesssensornodebasedonfpga
AT mingmeng onchipdlmsfilterdesignmethodofwirelesssensornodebasedonfpga
AT zepengliu onchipdlmsfilterdesignmethodofwirelesssensornodebasedonfpga