Echo-Signal De-Noising of CO<sub>2</sub>-DIAL Based on the Ensemble Empirical Mode Decomposition
The carbon dioxide (CO<sub>2</sub>) differential absorption lidar echo signal is susceptible to noise and must satisfy the high demand for signal-retrieval precision. Thus, a proper de-noising method should be selected to improve the inversion result. In this paper, we simultaneously dec...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/13/9/1361 |
| _version_ | 1797491351858708480 |
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| author | Chengzhi Xiang Yuxin Zheng Ailin Liang Ruizhe Li |
| author_facet | Chengzhi Xiang Yuxin Zheng Ailin Liang Ruizhe Li |
| author_sort | Chengzhi Xiang |
| collection | DOAJ |
| description | The carbon dioxide (CO<sub>2</sub>) differential absorption lidar echo signal is susceptible to noise and must satisfy the high demand for signal-retrieval precision. Thus, a proper de-noising method should be selected to improve the inversion result. In this paper, we simultaneously decompose three signal pairs into different intrinsic mode functions (IMFs) using the method of ensemble empirical mode decomposition (EEMD). Further, the correlation coefficients of the IMFs with the same temporal scale are regarded as the criterion to determine the components that need removal. This method not only retains the useful information effectively but also removes the noise component. A significant improvement in the R<sup>2</sup> of the differential absorption optical depth (DAOD) of the de-noised signals is obtained. The results of the simulated and observed analysis signal demonstrated improvement both in the SNR and in the retrieval precision. |
| first_indexed | 2024-03-10T00:47:09Z |
| format | Article |
| id | doaj.art-88aa5d2bfaae482781e712d569ca522c |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-10T00:47:09Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-88aa5d2bfaae482781e712d569ca522c2023-11-23T14:58:20ZengMDPI AGAtmosphere2073-44332022-08-01139136110.3390/atmos13091361Echo-Signal De-Noising of CO<sub>2</sub>-DIAL Based on the Ensemble Empirical Mode DecompositionChengzhi Xiang0Yuxin Zheng1Ailin Liang2Ruizhe Li3School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Geodesy and Geomatics, Wuhan University, Wuhan 430079, ChinaSchool of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaThe carbon dioxide (CO<sub>2</sub>) differential absorption lidar echo signal is susceptible to noise and must satisfy the high demand for signal-retrieval precision. Thus, a proper de-noising method should be selected to improve the inversion result. In this paper, we simultaneously decompose three signal pairs into different intrinsic mode functions (IMFs) using the method of ensemble empirical mode decomposition (EEMD). Further, the correlation coefficients of the IMFs with the same temporal scale are regarded as the criterion to determine the components that need removal. This method not only retains the useful information effectively but also removes the noise component. A significant improvement in the R<sup>2</sup> of the differential absorption optical depth (DAOD) of the de-noised signals is obtained. The results of the simulated and observed analysis signal demonstrated improvement both in the SNR and in the retrieval precision.https://www.mdpi.com/2073-4433/13/9/1361CO<sub>2</sub>-DIALecho-signal de-noisingensemble empirical mode decomposition |
| spellingShingle | Chengzhi Xiang Yuxin Zheng Ailin Liang Ruizhe Li Echo-Signal De-Noising of CO<sub>2</sub>-DIAL Based on the Ensemble Empirical Mode Decomposition Atmosphere CO<sub>2</sub>-DIAL echo-signal de-noising ensemble empirical mode decomposition |
| title | Echo-Signal De-Noising of CO<sub>2</sub>-DIAL Based on the Ensemble Empirical Mode Decomposition |
| title_full | Echo-Signal De-Noising of CO<sub>2</sub>-DIAL Based on the Ensemble Empirical Mode Decomposition |
| title_fullStr | Echo-Signal De-Noising of CO<sub>2</sub>-DIAL Based on the Ensemble Empirical Mode Decomposition |
| title_full_unstemmed | Echo-Signal De-Noising of CO<sub>2</sub>-DIAL Based on the Ensemble Empirical Mode Decomposition |
| title_short | Echo-Signal De-Noising of CO<sub>2</sub>-DIAL Based on the Ensemble Empirical Mode Decomposition |
| title_sort | echo signal de noising of co sub 2 sub dial based on the ensemble empirical mode decomposition |
| topic | CO<sub>2</sub>-DIAL echo-signal de-noising ensemble empirical mode decomposition |
| url | https://www.mdpi.com/2073-4433/13/9/1361 |
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