A Novel Lidar Signal-Denoising Algorithm Based on Sparrow Search Algorithm for Optimal Variational Modal Decomposition
Atmospheric lidar is susceptible to the influence of light attenuation, sky background light, and detector dark currents during the detection process. This results in a large amount of noise in the lidar return signal. To reduce noise and extract a useful signal, a novel denoising method combined wi...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/19/4960 |
| _version_ | 1797477133319143424 |
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| author | Zhiyuan Li Shun Li Jiandong Mao Juan Li Qiang Wang Yi Zhang |
| author_facet | Zhiyuan Li Shun Li Jiandong Mao Juan Li Qiang Wang Yi Zhang |
| author_sort | Zhiyuan Li |
| collection | DOAJ |
| description | Atmospheric lidar is susceptible to the influence of light attenuation, sky background light, and detector dark currents during the detection process. This results in a large amount of noise in the lidar return signal. To reduce noise and extract a useful signal, a novel denoising method combined with variational modal decomposition (VMD), the sparrow search algorithm (SSA) and singular value decomposition (SVD) is proposed. The SSA is used to optimize the number of decomposition layers <i>K</i> and the quadratic penalty factor <i>α</i> values of the VMD algorithm. Some intrinsic mode function (IMF) components obtained from the VMD-SSA decomposition are grouped and reconstructed according to the interrelationship number selection criterion. Then, the reconstructed signal is further denoised by combining the strong noise-reduction ability of SVD to obtain a clean lidar return signal. To verify the effectiveness of the VMD-SSA-SVD method, the method is compared and analysed with wavelet packet decomposition, empirical modal decomposition (EMD), ensemble empirical modal decomposition (EEMD), and adaptive noise-complete ensemble empirical modal decomposition (CEEMD), and its noise-reduction effect is considerably improved over that of the other four methods. The method can eliminate the complex noise in the lidar return signal while retaining all the details of the signal. The signal is not distorted, the waveform is smoother, and far-field noise interference can be suppressed. The denoised signal is closer to the real signal with higher accuracy, which shows the feasibility and the practicality of the proposed method. |
| first_indexed | 2024-03-09T21:13:17Z |
| format | Article |
| id | doaj.art-b7b38bdae6c64f6d8ca12ed62d1583d3 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T21:13:17Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-b7b38bdae6c64f6d8ca12ed62d1583d32023-11-23T21:41:33ZengMDPI AGRemote Sensing2072-42922022-10-011419496010.3390/rs14194960A Novel Lidar Signal-Denoising Algorithm Based on Sparrow Search Algorithm for Optimal Variational Modal DecompositionZhiyuan Li0Shun Li1Jiandong Mao2Juan Li3Qiang Wang4Yi Zhang5School of Electrical and Information Engineering, North Minzu University, North Wenchang Road, Yinchuan 750021, ChinaSchool of Electrical and Information Engineering, North Minzu University, North Wenchang Road, Yinchuan 750021, ChinaSchool of Electrical and Information Engineering, North Minzu University, North Wenchang Road, Yinchuan 750021, ChinaSchool of Electrical and Information Engineering, North Minzu University, North Wenchang Road, Yinchuan 750021, ChinaSchool of Electrical and Information Engineering, North Minzu University, North Wenchang Road, Yinchuan 750021, ChinaSchool of Electrical and Information Engineering, North Minzu University, North Wenchang Road, Yinchuan 750021, ChinaAtmospheric lidar is susceptible to the influence of light attenuation, sky background light, and detector dark currents during the detection process. This results in a large amount of noise in the lidar return signal. To reduce noise and extract a useful signal, a novel denoising method combined with variational modal decomposition (VMD), the sparrow search algorithm (SSA) and singular value decomposition (SVD) is proposed. The SSA is used to optimize the number of decomposition layers <i>K</i> and the quadratic penalty factor <i>α</i> values of the VMD algorithm. Some intrinsic mode function (IMF) components obtained from the VMD-SSA decomposition are grouped and reconstructed according to the interrelationship number selection criterion. Then, the reconstructed signal is further denoised by combining the strong noise-reduction ability of SVD to obtain a clean lidar return signal. To verify the effectiveness of the VMD-SSA-SVD method, the method is compared and analysed with wavelet packet decomposition, empirical modal decomposition (EMD), ensemble empirical modal decomposition (EEMD), and adaptive noise-complete ensemble empirical modal decomposition (CEEMD), and its noise-reduction effect is considerably improved over that of the other four methods. The method can eliminate the complex noise in the lidar return signal while retaining all the details of the signal. The signal is not distorted, the waveform is smoother, and far-field noise interference can be suppressed. The denoised signal is closer to the real signal with higher accuracy, which shows the feasibility and the practicality of the proposed method.https://www.mdpi.com/2072-4292/14/19/4960lidarsparrow search algorithmvariational modal decompositionsingular value decompositionnoise reduction |
| spellingShingle | Zhiyuan Li Shun Li Jiandong Mao Juan Li Qiang Wang Yi Zhang A Novel Lidar Signal-Denoising Algorithm Based on Sparrow Search Algorithm for Optimal Variational Modal Decomposition Remote Sensing lidar sparrow search algorithm variational modal decomposition singular value decomposition noise reduction |
| title | A Novel Lidar Signal-Denoising Algorithm Based on Sparrow Search Algorithm for Optimal Variational Modal Decomposition |
| title_full | A Novel Lidar Signal-Denoising Algorithm Based on Sparrow Search Algorithm for Optimal Variational Modal Decomposition |
| title_fullStr | A Novel Lidar Signal-Denoising Algorithm Based on Sparrow Search Algorithm for Optimal Variational Modal Decomposition |
| title_full_unstemmed | A Novel Lidar Signal-Denoising Algorithm Based on Sparrow Search Algorithm for Optimal Variational Modal Decomposition |
| title_short | A Novel Lidar Signal-Denoising Algorithm Based on Sparrow Search Algorithm for Optimal Variational Modal Decomposition |
| title_sort | novel lidar signal denoising algorithm based on sparrow search algorithm for optimal variational modal decomposition |
| topic | lidar sparrow search algorithm variational modal decomposition singular value decomposition noise reduction |
| url | https://www.mdpi.com/2072-4292/14/19/4960 |
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