FIR, IIR and Wavelet Algorithms for the Rigorous Filtering of GOCE SGG Data to the GOCE MBW
Gravity field and steady-state Ocean Circulation Explorer (GOCE) data are strongly affected by noise and long-wavelength errors outside the satellite measurement bandwidth (MBW). One of the main goals in utilizing GOCE data for gravity field modeling is the application of filtering techniques that c...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/13/3024 |
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| author | Eleftherios Pitenis Elisavet Mamagiannou Dimitrios A. Natsiopoulos Georgios S. Vergos Ilias N. Tziavos Vassilios N. Grigoriadis Michael G. Sideris |
| author_facet | Eleftherios Pitenis Elisavet Mamagiannou Dimitrios A. Natsiopoulos Georgios S. Vergos Ilias N. Tziavos Vassilios N. Grigoriadis Michael G. Sideris |
| author_sort | Eleftherios Pitenis |
| collection | DOAJ |
| description | Gravity field and steady-state Ocean Circulation Explorer (GOCE) data are strongly affected by noise and long-wavelength errors outside the satellite measurement bandwidth (MBW). One of the main goals in utilizing GOCE data for gravity field modeling is the application of filtering techniques that can remove gross errors and reduce low-frequency errors and high-frequency noise while preserving the original signal. This paper aims to present and analyze three filtering strategies used to de-noise the GOCE Level 2 data from long-wavelength correlated errors and noise. These strategies are Finite Impulse Response (FIR), Infinite Impulse Response (IIR), and Wavelet Multi-resolution Analysis (WL), which have been applied to GOCE residual second order derivatives of the gravity potential. Several experiments were performed for each filtering scheme in order to identify the ideal filtering parameters. The outcomes indicate that all the suggested filtering strategies proved to be effective in removing low-frequency errors while preserving the signals in the GOCE MBW, with FIR filtering providing the overall best results. |
| first_indexed | 2024-03-09T03:56:47Z |
| format | Article |
| id | doaj.art-af35d38ca3494846bf1c927defcfd110 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T03:56:47Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-af35d38ca3494846bf1c927defcfd1102023-12-03T14:19:58ZengMDPI AGRemote Sensing2072-42922022-06-011413302410.3390/rs14133024FIR, IIR and Wavelet Algorithms for the Rigorous Filtering of GOCE SGG Data to the GOCE MBWEleftherios Pitenis0Elisavet Mamagiannou1Dimitrios A. Natsiopoulos2Georgios S. Vergos3Ilias N. Tziavos4Vassilios N. Grigoriadis5Michael G. Sideris6Laboratory of Gravity Field Research and Applications (GravLab), Department of Geodesy and Surveying, Aristotle University of Thessaloniki, University Box 440, GR-54124 Thessaloniki, GreeceLaboratory of Gravity Field Research and Applications (GravLab), Department of Geodesy and Surveying, Aristotle University of Thessaloniki, University Box 440, GR-54124 Thessaloniki, GreeceLaboratory of Gravity Field Research and Applications (GravLab), Department of Geodesy and Surveying, Aristotle University of Thessaloniki, University Box 440, GR-54124 Thessaloniki, GreeceLaboratory of Gravity Field Research and Applications (GravLab), Department of Geodesy and Surveying, Aristotle University of Thessaloniki, University Box 440, GR-54124 Thessaloniki, GreeceLaboratory of Gravity Field Research and Applications (GravLab), Department of Geodesy and Surveying, Aristotle University of Thessaloniki, University Box 440, GR-54124 Thessaloniki, GreeceLaboratory of Gravity Field Research and Applications (GravLab), Department of Geodesy and Surveying, Aristotle University of Thessaloniki, University Box 440, GR-54124 Thessaloniki, GreeceDepartment of Geomatics Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, CanadaGravity field and steady-state Ocean Circulation Explorer (GOCE) data are strongly affected by noise and long-wavelength errors outside the satellite measurement bandwidth (MBW). One of the main goals in utilizing GOCE data for gravity field modeling is the application of filtering techniques that can remove gross errors and reduce low-frequency errors and high-frequency noise while preserving the original signal. This paper aims to present and analyze three filtering strategies used to de-noise the GOCE Level 2 data from long-wavelength correlated errors and noise. These strategies are Finite Impulse Response (FIR), Infinite Impulse Response (IIR), and Wavelet Multi-resolution Analysis (WL), which have been applied to GOCE residual second order derivatives of the gravity potential. Several experiments were performed for each filtering scheme in order to identify the ideal filtering parameters. The outcomes indicate that all the suggested filtering strategies proved to be effective in removing low-frequency errors while preserving the signals in the GOCE MBW, with FIR filtering providing the overall best results.https://www.mdpi.com/2072-4292/14/13/3024GOCEFIRIIRwaveletsfilteringMBW |
| spellingShingle | Eleftherios Pitenis Elisavet Mamagiannou Dimitrios A. Natsiopoulos Georgios S. Vergos Ilias N. Tziavos Vassilios N. Grigoriadis Michael G. Sideris FIR, IIR and Wavelet Algorithms for the Rigorous Filtering of GOCE SGG Data to the GOCE MBW Remote Sensing GOCE FIR IIR wavelets filtering MBW |
| title | FIR, IIR and Wavelet Algorithms for the Rigorous Filtering of GOCE SGG Data to the GOCE MBW |
| title_full | FIR, IIR and Wavelet Algorithms for the Rigorous Filtering of GOCE SGG Data to the GOCE MBW |
| title_fullStr | FIR, IIR and Wavelet Algorithms for the Rigorous Filtering of GOCE SGG Data to the GOCE MBW |
| title_full_unstemmed | FIR, IIR and Wavelet Algorithms for the Rigorous Filtering of GOCE SGG Data to the GOCE MBW |
| title_short | FIR, IIR and Wavelet Algorithms for the Rigorous Filtering of GOCE SGG Data to the GOCE MBW |
| title_sort | fir iir and wavelet algorithms for the rigorous filtering of goce sgg data to the goce mbw |
| topic | GOCE FIR IIR wavelets filtering MBW |
| url | https://www.mdpi.com/2072-4292/14/13/3024 |
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