Performance of BDS Navigation Ionospheric Model During the Main Phase of Different Classified Geomagnetic Storms in China Region

© 2020. American Geophysical Union. All Rights Reserved. Geomagnetic storms can have a great impact on the Earth's upper atmosphere, that is, the ionosphere. The activity of the ionosphere could be more pronounced during geomagnetic storms, which can make key ionospheric parameters, like total electron content (TEC), very hard to be modeled. The use of a Global Navigation Satellite System (GNSS) navigation ionospheric model is a conventional option for users to correct the ionospheric delay, which could suffer from the effects of storms. In this study, the performance of Beidou Navigation Satellite System (BDS) navigation ionospheric model in the China region during the main phase of different classes of geomagnetic storms is investigated for the first time. The analysis of the results revealed that the accuracy of the BDS navigation ionospheric model was impacted to different degrees during the storms. The effects during strong storms were the greatest, followed by moderate and weak storms. The impact on the accuracy of the model was characterized by latitude and local time. Furthermore, the accuracy of the model during the same class of storms was not always at the same level. The finding in this study could benefit the prediction of GNSS navigation ionospheric models' performance during geomagnetic storms

Orbit determination and prediction accuracy analysis for a regional tracking network

China's COMPASS satellite navigation system relies on a regional tracking network to provide navigation services. Limited by its geographic border, the regional network is able to cover only 30% of the medium-earth-orbits (MEO). Accuracy of determined and predicted orbits is not able to satisfy system requirements if the tracking data processing strategy for global tracking network processing is used for the regional network. Two major error sources for orbital prediction are accuracy of initial orbital elements and dynamical modeling. To achieve better prediction accuracy, we propose a two-step orbit determination and prediction strategy. For step 1, only solar radiation pressure (SRP) parameters are estimated along with the orbital elements and other parameters; for step 2, all parameters are estimated but the SRP parameters are tightly constrained to their step 1 estimates. Experimenting with data from a regional GPS network, we conclude for orbital prediction using the proposed two-step strategy, the average user range error (URE) for 24-h prediction arcs is better than 0.6 m

Timing performance evaluation of Radio Determination Satellite Service (RDSS) for Beidou system

Radio Determination Satellite Service (RDSS) is the advantage and particular characteristics of Beidou, which is different from other satellite navigation systems. According to the rare existing researches of its timing service, this article evaluates timing performance of one-way and two-way using the time series analysis method. Moreover, this paper systematically studies the one-way timing and two-way timing principle and introduces Beidou measured data and analysis method. By analyzing the clock error total curve, the mean value segment, noise situation and timing accuracy, we have the conclusions: (1) one-way timing accuracy is less than 30 ns, and its Root Mean Square (RMS) is less than 6.81 ns; (2) two-way timing accuracy is less than 20 ns, and its Root Mean Square (RMS) is less than 3.60 ns; (3) there exist period switching phenomenon of timing data of one-way and two-way in each beam, and stratification of one-way timing data. These conclusions can be used for the difference compensation of Radio Determination Satellite Service (RDSS), which can provide reference for the clock error consistency of Beidou system, and then improve the system service precision

Long-Term Water Storage Changes of Lake Volta from GRACE and Satellite Altimetry and Connections with Regional Climate

Satellite gravity data from the Gravity Recovery and Climate Experiment (GRACE) provides a quantitative measure of terrestrial water storage (TWS) change at different temporal and spatial scales. In this study, we investigate the ability of GRACE to quantitatively monitor long-term hydrological characteristics over the Lake Volta region. Principal component analysis (PCA) is employed to study temporal and spatial variability of long-term TWS changes. Long-term Lake Volta water storage change appears to be the dominant long-term TWS change signal in the Volta basin. GRACE-derived TWS changes and precipitation variations compiled by the Global Precipitation Climatology Centre (GPCC) are related both temporally and spatially, but spatial leakage attenuates the magnitude of GRACE estimates, especially at small regional scales. Using constrained forward modeling, we successfully remove leakage error in GRACE estimates. After this leakage correction, GRACE-derived Lake Volta water storage changes agree remarkably well with independent estimates from satellite altimetry at interannual and longer time scales. This demonstrates the value of GRACE estimates to monitor and quantify water storage changes in lakes, especially in relatively small regions with complicated topography