Analysis of the DORIS contributions to ITRF2008

Angermann, D; Seitz, M.; Drewes, H

doi:10.1016/j.asr.2010.07.018

Cited by 9 publications

(5 citation statements)

References 23 publications

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“…Accurate EOP can be measured from space-geodetic techniques such as Very Long Baseline Interferometry (VLBI) [6][7][8][9], Global Navigation Satellite System (GNSS) [10][11][12][13], Satellite Laser Ranging (SLR) [14], Lunar Laser Ranging (LLR) [15,16], and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) [17][18][19]. However, the determination of EOP is often delayed by several days or even weeks due to the large volume of observation data, and complex data processing procedures.…”

Section: Introductionmentioning

confidence: 99%

Research on UT1-UTC and LOD Prediction Algorithm Based on Denoised EAM Dataset

Li,

Wu,

Yao

et al. 2023

Remote Sensing

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The components of EAM are strongly correlated with LOD and play an important role in UT1-UTC and LOD prediction. However, the EAM dataset is prone to be noisy. In this study, we propose a hybrid method to reduce the noise of the EAM data and improve the accuracy of UT1-UTC and LOD predictions. We use the EOP data to denoise the EAM data, and use Kalman filtering to denoise the 1–6 days forecast of EAM. Then, we use the denoised EAM dataset to improve the UT1-UTC and LOD prediction. The denoised EAM dataset improved the prediction of UT1-UTC within 10 days by 20%. In addition, we found that by introducing two additional periodic (23.9 days and 91.3 days) components for the least-squares fitting, the accuracy of UT1-UTC and LOD prediction in the range of 30–80 days is significantly improved. In more than 430 UT1-UTC and LOD prediction experiments conducted during 2021–2022, the improvements in the 1–6 days forecast were significant. For the 6th day, 30th day, and 60th day, the MAE of UT1-UTC was 0.1592, 2.9169, and 6.7857 ms, respectively, corresponding to improvements of 31.35, 12.60, and 12.93%, respectively, when compared to predictions of Bulletin A. The MAE of LOD predictions on the 1st day, 6th day, 30th day, and 90th day was 0.0255, 0.0432, 0.1694, and 0.2505 ms, respectively, which improved by 26.09, 14.29, 6.36, and 3.76% when compared with our second EOPPCC method.

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Section: Introductionmentioning

confidence: 99%

Research on UT1-UTC and LOD Prediction Algorithm Based on Denoised EAM Dataset

Li,

Wu,

Yao

et al. 2023

Remote Sensing

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“…The five Earth Orientation Parameters (EOP), comprising nutation or celestial pole offsets (CPO), polar motion (PM), and differences between universal time and coordinated universal time (UT1-UTC; or its time-derivative Length-of-Day (LOD) change), describe the time-variable rotation of our planet and link the terrestrial and the celestial reference frames. EOP are regularly measured by modern space-geodetic techniques, such as very long baseline interferometry (VLBI, Nilsson et al 2010Nilsson et al , 2011Nilsson et al , 2014, global navigation satellite systems (GNSS, Byram and Hackman 2012;Mireault et al 1999;Zajdel et al 2020), satellite laser ranging (SLR, Coulot et al 2010), lunar laser ranging (LLR, Pavlov 2020), and Doppler orbitography and radiopositioning integrated by satellites (DORIS, Angermann et al 2010;Moreaux et al 2016). The current accuracy of EOP determination is about 0.05 mas (milliarcseconds), which corresponds to 1.5 mm of horizontal displacement on the Earth's surface (Petit and Luzum 2010).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of selected short-term predictions of UT1-UTC and LOD collected in the second earth orientation parameters prediction comparison campaign

Kur

Dobslaw

Śliwińska

et al. 2022

Earth Planets Space

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Advanced geodetic and astronomical tasks, such as precise positioning and navigation require forecasted Earth Orientation Parameters (EOP). The Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC) aims to compare various EOP forecast methods implemented by different institutes from all over the world. Here we focus on universal time (UT1-UTC) and Length-of-Day (LOD) predictions received in the period between September 1st, 2021 and May 29th, 2022. The forecasts are preliminarily evaluated against the EOP 14 C04 solution delivered by the International Earth Rotation and Reference System Service (IERS) by using the mean absolute error (MAE) as the prediction quality measure. Exemplarily, we compare forecasts from IERS delivered by U.S. Naval Observatory (USNO) and a selected campaign participant to assess the impact of both input data and computation methodology on predictions. We show that improper treatment of long-periodic ocean tides has severely degraded LOD forecasting until this issue has been brought to the attention of the participant during a meeting of the 2nd EOP PCC. We consider this as a good example for the benefit of the campaign to the overall scientific community by providing specific feedback to individual processing centres on deficits in their products, which lead to quick and effective adaptations. The lessons learned from this analysis could be applied to other EOP forecasting methods based on Effective Angular Momentum (EAM) predictions. Graphical Abstract

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“…1985), Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) (Angermann et al. 2010), Global Navigation Satellite Systems (GNSS) (Dow et al. 2009; Byram and Hackman 2012), and very-long-baseline interferometry (VLBI) (Schuh and Schmitz-Hübsch 2000; Nilsson et al.…”

Section: Introductionmentioning

confidence: 99%

Polar motion prediction using the combination of SSA and Copula-based analysis

Modiri

Belda

Heinkelmann

et al. 2018

Earth Planets Space

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The real-time estimation of polar motion (PM) is needed for the navigation of Earth satellite and interplanetary spacecraft. However, it is impossible to have real-time information due to the complexity of the measurement model and data processing. Various prediction methods have been developed. However, the accuracy of PM prediction is still not satisfactory even for a few days in the future. Therefore, new techniques or a combination of the existing methods need to be investigated for improving the accuracy of the predicted PM. There is a well-introduced method called Copula, and we want to combine it with singular spectrum analysis (SSA) method for PM prediction. In this study, first, we model the predominant trend of PM time series using SSA. Then, the difference between PM time series and its SSA estimation is modeled using Copula-based analysis. Multiple sets of PM predictions which range between 1 and 365 days have been performed based on an IERS 08 C04 time series to assess the capability of our hybrid model. Our results illustrate that the proposed method can efficiently predict PM. The improvement in PM prediction accuracy up to 365 days in the future is found to be around 40% on average and up to 65 and 46% in terms of success rate for the and , respectively.

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Analysis of the DORIS contributions to ITRF2008

Cited by 9 publications

References 23 publications

Research on UT1-UTC and LOD Prediction Algorithm Based on Denoised EAM Dataset

Research on UT1-UTC and LOD Prediction Algorithm Based on Denoised EAM Dataset

Evaluation of selected short-term predictions of UT1-UTC and LOD collected in the second earth orientation parameters prediction comparison campaign

Polar motion prediction using the combination of SSA and Copula-based analysis

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