The Impact of Different Filters on the Gravity Field Recovery Based on the GOCE Gradient Data
The electrostatic gravity gradiometer carried by the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite is affected by accelerometer noise and other factors; hence, the observation data present complex error characteristics in the low-frequency domain. The accuracy of the rec...
| Main Authors: | , , , , |
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| Format: | Article |
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MDPI AG
2023-10-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/20/5034 |
| _version_ | 1797572394617929728 |
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| author | Qinglu Mu Changqing Wang Min Zhong Yihao Yan Lei Liang |
| author_facet | Qinglu Mu Changqing Wang Min Zhong Yihao Yan Lei Liang |
| author_sort | Qinglu Mu |
| collection | DOAJ |
| description | The electrostatic gravity gradiometer carried by the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite is affected by accelerometer noise and other factors; hence, the observation data present complex error characteristics in the low-frequency domain. The accuracy of the recovered gravity field will be directly affected by the design of the filters based on the error characteristics of the gradient data. In this study, the applicability of various filters to different errors in observation is evaluated, such as the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mo>/</mo><mi>f</mi></mrow></semantics></math></inline-formula> error and the orbital frequency errors. The experimental results show that the cascade filter (DARMA), which is formed of a differential filter and an autoregressive moving average filter (ARMA) filter, has the best accuracy for the characteristic of the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mo>/</mo><mi>f</mi></mrow></semantics></math></inline-formula> low-frequency error. The strategy of introducing empirical parameters can reduce the orbital frequency errors, whereas the application of a notch filter will worsen the final solution. Frequent orbit changes and other changes in the observed environment have little impact on the new version gradient data (the data product is coded 0202), while the influence cannot be ignored on the results of the old version data (the data product is coded 0103). The influence can be effectively minimized by shortening the length of the arc. By analyzing the above experimental findings, it can be concluded that the inversion accuracy can be effectively improved by choosing the appropriate filter combination and filter estimation frequency when solving the gravity field model based on the gradient data of the GOCE satellite. This is of reference significance for the updating of the existing models. |
| first_indexed | 2024-03-10T20:55:38Z |
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| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T20:55:38Z |
| publishDate | 2023-10-01 |
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| series | Remote Sensing |
| spelling | doaj.art-602667d9ad0d4279a85d2eb3cec7a1812023-11-19T17:59:55ZengMDPI AGRemote Sensing2072-42922023-10-011520503410.3390/rs15205034The Impact of Different Filters on the Gravity Field Recovery Based on the GOCE Gradient DataQinglu Mu0Changqing Wang1Min Zhong2Yihao Yan3Lei Liang4State Key Laboratory of Geodesy and Earth’s Dynamics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430077, ChinaState Key Laboratory of Geodesy and Earth’s Dynamics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430077, ChinaSchool of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, ChinaMax-Planck-Institut für Gravitationsphysik (Albert-Einstein-Institut) and Institut für Gravitationsphysik, Leibniz Universität Hannover, 30167 Hannover, GermanySchool of Geographic Information and Tourism, Chuzhou University, Chuzhou 239000, ChinaThe electrostatic gravity gradiometer carried by the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite is affected by accelerometer noise and other factors; hence, the observation data present complex error characteristics in the low-frequency domain. The accuracy of the recovered gravity field will be directly affected by the design of the filters based on the error characteristics of the gradient data. In this study, the applicability of various filters to different errors in observation is evaluated, such as the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mo>/</mo><mi>f</mi></mrow></semantics></math></inline-formula> error and the orbital frequency errors. The experimental results show that the cascade filter (DARMA), which is formed of a differential filter and an autoregressive moving average filter (ARMA) filter, has the best accuracy for the characteristic of the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mo>/</mo><mi>f</mi></mrow></semantics></math></inline-formula> low-frequency error. The strategy of introducing empirical parameters can reduce the orbital frequency errors, whereas the application of a notch filter will worsen the final solution. Frequent orbit changes and other changes in the observed environment have little impact on the new version gradient data (the data product is coded 0202), while the influence cannot be ignored on the results of the old version data (the data product is coded 0103). The influence can be effectively minimized by shortening the length of the arc. By analyzing the above experimental findings, it can be concluded that the inversion accuracy can be effectively improved by choosing the appropriate filter combination and filter estimation frequency when solving the gravity field model based on the gradient data of the GOCE satellite. This is of reference significance for the updating of the existing models.https://www.mdpi.com/2072-4292/15/20/5034earth’s static gravity fieldGOCEfilter design |
| spellingShingle | Qinglu Mu Changqing Wang Min Zhong Yihao Yan Lei Liang The Impact of Different Filters on the Gravity Field Recovery Based on the GOCE Gradient Data Remote Sensing earth’s static gravity field GOCE filter design |
| title | The Impact of Different Filters on the Gravity Field Recovery Based on the GOCE Gradient Data |
| title_full | The Impact of Different Filters on the Gravity Field Recovery Based on the GOCE Gradient Data |
| title_fullStr | The Impact of Different Filters on the Gravity Field Recovery Based on the GOCE Gradient Data |
| title_full_unstemmed | The Impact of Different Filters on the Gravity Field Recovery Based on the GOCE Gradient Data |
| title_short | The Impact of Different Filters on the Gravity Field Recovery Based on the GOCE Gradient Data |
| title_sort | impact of different filters on the gravity field recovery based on the goce gradient data |
| topic | earth’s static gravity field GOCE filter design |
| url | https://www.mdpi.com/2072-4292/15/20/5034 |
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