An Ice-Penetrating Signal Denoising Method Based on WOA-VMD-BD
Chang’E-7 will be launched around 2026 to explore resources at the lunar south pole. Glaciers are suitable scenes on the earth for lunar penetrating radar verification. In the verification experiment, ice-penetrating signals are inevitably polluted by noise, affecting the accuracy and reliability of...
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2023
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Online Access: | https://doi.org/10.3390/electronics12071658 https://doaj.org/article/844e6c37b9714ff7a846f53d0bd93428 |
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ftdoajarticles:oai:doaj.org/article:844e6c37b9714ff7a846f53d0bd93428 2023-06-06T11:59:22+02:00 An Ice-Penetrating Signal Denoising Method Based on WOA-VMD-BD Danping Lu Shaoxiang Shen Yuxi Li Bo Zhao Xiaojun Liu Guangyou Fang 2023-03-01T00:00:00Z https://doi.org/10.3390/electronics12071658 https://doaj.org/article/844e6c37b9714ff7a846f53d0bd93428 EN eng MDPI AG https://www.mdpi.com/2079-9292/12/7/1658 https://doaj.org/toc/2079-9292 doi:10.3390/electronics12071658 2079-9292 https://doaj.org/article/844e6c37b9714ff7a846f53d0bd93428 Electronics, Vol 12, Iss 1658, p 1658 (2023) ice-penetrating signal VMD WOA BD parameter optimization IMFs Electronics TK7800-8360 article 2023 ftdoajarticles https://doi.org/10.3390/electronics12071658 2023-04-16T00:33:52Z Chang’E-7 will be launched around 2026 to explore resources at the lunar south pole. Glaciers are suitable scenes on the earth for lunar penetrating radar verification. In the verification experiment, ice-penetrating signals are inevitably polluted by noise, affecting the accuracy and reliability of glacier detection. This paper proposes a denoising method for ice-penetrating signals based on the combination of whale optimization algorithm (WOA), variational mode decomposition (VMD), and the improved Bhattacharyya distance (BD). Firstly, a fitness function for WOA is established based on permutation entropy (PE), and the number of decomposition modes K and the quadratic penalty factor <semantics> α </semantics> in the VMD are optimized using WOA. Then, VMD is performed on the signal to obtain multiple intrinsic mode functions (IMFs). Finally, according to the BD, the relevant IMFs are selected for signal reconstruction and denoising. The simulation results indicate the strengths of this method in enhancing the signal-to-noise ratio (SNR), and its performance is better than empirical mode decomposition (EMD). Experiments on the detected signals of the Mengke Glacier No. 29 indicate that the WOA-VMD-BD method can efficiently eliminate noise from the data and procure well-defined layered profiles of the glacier. The research in this paper helps observe the layered details of the lunar regolith profile and interpret the data in subsequent space exploration missions. Article in Journal/Newspaper South pole Directory of Open Access Journals: DOAJ Articles South Pole Electronics 12 7 1658 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
ice-penetrating signal VMD WOA BD parameter optimization IMFs Electronics TK7800-8360 |
spellingShingle |
ice-penetrating signal VMD WOA BD parameter optimization IMFs Electronics TK7800-8360 Danping Lu Shaoxiang Shen Yuxi Li Bo Zhao Xiaojun Liu Guangyou Fang An Ice-Penetrating Signal Denoising Method Based on WOA-VMD-BD |
topic_facet |
ice-penetrating signal VMD WOA BD parameter optimization IMFs Electronics TK7800-8360 |
description |
Chang’E-7 will be launched around 2026 to explore resources at the lunar south pole. Glaciers are suitable scenes on the earth for lunar penetrating radar verification. In the verification experiment, ice-penetrating signals are inevitably polluted by noise, affecting the accuracy and reliability of glacier detection. This paper proposes a denoising method for ice-penetrating signals based on the combination of whale optimization algorithm (WOA), variational mode decomposition (VMD), and the improved Bhattacharyya distance (BD). Firstly, a fitness function for WOA is established based on permutation entropy (PE), and the number of decomposition modes K and the quadratic penalty factor <semantics> α </semantics> in the VMD are optimized using WOA. Then, VMD is performed on the signal to obtain multiple intrinsic mode functions (IMFs). Finally, according to the BD, the relevant IMFs are selected for signal reconstruction and denoising. The simulation results indicate the strengths of this method in enhancing the signal-to-noise ratio (SNR), and its performance is better than empirical mode decomposition (EMD). Experiments on the detected signals of the Mengke Glacier No. 29 indicate that the WOA-VMD-BD method can efficiently eliminate noise from the data and procure well-defined layered profiles of the glacier. The research in this paper helps observe the layered details of the lunar regolith profile and interpret the data in subsequent space exploration missions. |
format |
Article in Journal/Newspaper |
author |
Danping Lu Shaoxiang Shen Yuxi Li Bo Zhao Xiaojun Liu Guangyou Fang |
author_facet |
Danping Lu Shaoxiang Shen Yuxi Li Bo Zhao Xiaojun Liu Guangyou Fang |
author_sort |
Danping Lu |
title |
An Ice-Penetrating Signal Denoising Method Based on WOA-VMD-BD |
title_short |
An Ice-Penetrating Signal Denoising Method Based on WOA-VMD-BD |
title_full |
An Ice-Penetrating Signal Denoising Method Based on WOA-VMD-BD |
title_fullStr |
An Ice-Penetrating Signal Denoising Method Based on WOA-VMD-BD |
title_full_unstemmed |
An Ice-Penetrating Signal Denoising Method Based on WOA-VMD-BD |
title_sort |
ice-penetrating signal denoising method based on woa-vmd-bd |
publisher |
MDPI AG |
publishDate |
2023 |
url |
https://doi.org/10.3390/electronics12071658 https://doaj.org/article/844e6c37b9714ff7a846f53d0bd93428 |
geographic |
South Pole |
geographic_facet |
South Pole |
genre |
South pole |
genre_facet |
South pole |
op_source |
Electronics, Vol 12, Iss 1658, p 1658 (2023) |
op_relation |
https://www.mdpi.com/2079-9292/12/7/1658 https://doaj.org/toc/2079-9292 doi:10.3390/electronics12071658 2079-9292 https://doaj.org/article/844e6c37b9714ff7a846f53d0bd93428 |
op_doi |
https://doi.org/10.3390/electronics12071658 |
container_title |
Electronics |
container_volume |
12 |
container_issue |
7 |
container_start_page |
1658 |
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1767949300523859968 |