Details
| Original language | English |
|---|---|
| Article number | 5034 |
| Number of pages | 19 |
| Journal | Remote sensing |
| Volume | 15 |
| Issue number | 20 |
| Publication status | Published - 20 Oct 2023 |
Abstract
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 (Formula presented.) 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 (Formula presented.) 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.
Keywords
- earth’s static gravity field, filter design, GOCE
ASJC Scopus subject areas
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In: Remote sensing, Vol. 15, No. 20, 5034, 20.10.2023.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - The Impact of Different Filters on the Gravity Field Recovery Based on the GOCE Gradient Data
AU - Mu, Qinglu
AU - Wang, Changqing
AU - Zhong, Min
AU - Yan, Yihao
AU - Liang, Lei
N1 - This research was funded by the National Natural Science Foundation of China (Grants No. 42174103, No. 12261131504, No. 42027802, and No. 42204091), the National Key R&D Program of China (Grant No. 2022YFC2204601), the Open Fund of Hubei Luojia Laboratory (Grant No. 220100044).
PY - 2023/10/20
Y1 - 2023/10/20
N2 - 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 (Formula presented.) 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 (Formula presented.) 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.
AB - 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 (Formula presented.) 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 (Formula presented.) 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.
KW - earth’s static gravity field
KW - filter design
KW - GOCE
UR - http://www.scopus.com/inward/record.url?scp=85175365241&partnerID=8YFLogxK
U2 - 10.3390/rs15205034
DO - 10.3390/rs15205034
M3 - Article
AN - SCOPUS:85175365241
VL - 15
JO - Remote sensing
JF - Remote sensing
SN - 2072-4292
IS - 20
M1 - 5034
ER -