Frequency Analysis and Filtering Processing of Gravity Gradient Data from GOCE

Wan, Xiaoqiao; Yu, Jian; Zeng, Yanyan

doi:10.1002/cjg2.1747

Cited by 8 publications

(4 citation statements)

References 16 publications

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“…These must then be filtered because the GOCE GGs are band-limited measurements. A forward and backward finite impulse response band-pass filter is used to account for the band-limited measurements according to Wan et al (2012). This approach can also eliminate phase change after filtering.…”

Section: Preprocessingmentioning

confidence: 99%

“…In this way, it avoids to filter both sides of the observations and the columns of the design matrix during calculations like the time-wise approach and the direct approach. This kind of filtering and replacement method can be used both for spherical harmonic analysis and direct least squares method according to Wan et al (2012). Therefore the final gravity field model built in this paper is practically a combined one which is improved by GOCE GGs signals from the a-priori gravity field model.…”

Section: Introductionmentioning

confidence: 99%

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The gravity field model IGGT_R1 based on the second invariant of the GOCE gravitational gradient tensor

Luo

Zhong

et al. 2017

J Geod

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Based on tensor theory, three Invariants of the Gravitational Gradient Tensor (IGGT) are independent of the Gradiometer Reference Frame (GRF). Compared to traditional methods for calculation of gravity field models based on the Gravity field and steady-state Ocean Circulation Explorer (GOCE) data, which are affected by errors in the attitude indicator, using IGGT and least squares method avoids the problem of inaccurate rotation matrices. The IGGT approach as studied in this paper is a quadratic function of the gravity field model's spherical harmonic coefficients. The linearized observation equations for the least squares method is obtained using a Taylor expansion, and the weighting equation is derived using the law of error propagation. We also investigate the linearization errors using existing gravity field models and find that this error can be ignored since the used a-priori model EIGEN-5C is sufficiently accurate. One problem when using this approach is that it needs all six independent Gravitational Gradients (GGs), but the components V xy and V yz of GOCE are worse due to the non-sensitive axes of the GOCE gradiometer. Therefore we use synthetic GGs for both inaccurate gravitational gradient components derived from the a-priori gravity field model EIGEN-5C. Another problem is that the GOCE GGs are measured in a band-limited manner. Therefore, a forward and backward finite impulse response band-pass filter is applied to the data, which can also eliminate filter caused phase change. The Spherical Cap Regularization Approach (SCRA) and the Kaula rule are then applied to solve the polar gap problem caused by GOCE's inclination of 96.7 0. With the techniques described above, a degree/order 240 gravity field model called IGGT R1 is computed. Since the synthetic components of V xy and V yz are not band-pass filtered, the signals outside the measurement bandwidth are replaced by the a-priori model EIGEN-5C. Therefore this model is practically a combined gravity field model which contains GOCE GGs signals and long wavelength signals from the a-priori model EIGEN-5C. Finally, IGGT R1's accuracy is evaluated by comparison with other gravity field models in terms of difference degree amplitudes, the geostrophic velocity in the Agulhas current area, gravity anomaly differences as well as by comparison to GNSS/Leveling data.

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Section: Preprocessingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The gravity field model IGGT_R1 based on the second invariant of the GOCE gravitational gradient tensor

Luo

Zhong

et al. 2017

J Geod

View full text Add to dashboard Cite

show abstract

“…The third method is similar to the second method's conceptual design, but with the difference that it requires immediate processing with band-pass filters, such as FIR (Finite Impulse Response) filtering (Wan, et al. [38]) or IIR (Infinite Impulse Response) band-pass filter. Pitenis, et al [39] analyzed the effectiveness of three filters, FIR, IIR, and wavelet multiresolution analysis.…”

Section: Introductionmentioning

confidence: 99%

“…In addition to the previous conclusions, the analysis of the results reveals that: (1) Although both BP1 and BP2 utilized bandpass filters, BP1's total cumulative error is 25% lower than BP2's due to different cutoff frequencies. The filter cutoff frequency of BP2 is related to the maximum degree of solution [38], conforming to the relationship: N = f T, where f is the cutoff frequency, T is the satellite orbital period, and N is the maximum degree of the gravity field. In contrast, BP1 retains the signal in the 5~100 MHz bandwidth.…”

mentioning

confidence: 99%

The Impact of Different Filters on the Gravity Field Recovery Based on the GOCE Gradient Data

Mu,

Wang,

Zhong

et al. 2023

Remote Sensing

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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 1/f 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 1/f 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.

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Adaptive filtering of GOCE-derived gravity gradients of the disturbing potential in the context of the space-wise approach

Piretzidis

Sideris

2017

J Geod

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Frequency Analysis and Filtering Processing of Gravity Gradient Data from GOCE

Cited by 8 publications

References 16 publications

The gravity field model IGGT_R1 based on the second invariant of the GOCE gravitational gradient tensor

The gravity field model IGGT_R1 based on the second invariant of the GOCE gravitational gradient tensor

The Impact of Different Filters on the Gravity Field Recovery Based on the GOCE Gradient Data

Adaptive filtering of GOCE-derived gravity gradients of the disturbing potential in the context of the space-wise approach

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