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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2020/4850438 |
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| _version_ | 1849467786645995520 |
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| 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 |
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