Progress of Geodesy Related Ionosphere from Chinese Scientists in the Period of 2019—2023

The ionosphere is the ionized part of the upper atmosphere of the Earth,which plays an important role in atmospheric electricity and forms the inner edge of the magnetosphere.It influences radio propagation significantly,such as the Global Navigation Satellite System(GNSS).Meanwhile,the GNSS is also an essential technique for sensing the variation of ionosphere.During the years of 2019—2023,a large number of Chinese geodesy scientists devoted much efforts to the geodesy related ionosphere.Due to the very limited length,the achievements are carried out from the following six aspects,including:①The ionospheric correction models for BDS and BDSBAS;②Real-time global ionospheric monitoring and modeling;③The ionospheric 2D and 3D modeling based on GNSS and LEO satellites;④The ionospheric prediction based on artificial intelligence;⑤The monitoring and mitigation of ionospheric disturbances for GNSS users;⑥The ionospheric related data products and classical applications.

Safety Performance of a Precast Concrete Barrier: Numerical Study

The numerical simulation for a new type of precast concrete barrier for viaducts is carried out systematically.To obtain an accurate representation of the damage state of the concrete barrier under the impact of a vehicle,a stochastic damage-plasticity model of the concrete is adopted in the finite element model.Meanwhile,a simplified mathematical model of the impact between vehicles and the concrete barrier was established and the input energy was converted to the impact load to facilitate the investigation of the safety performance of the concrete barriers.On this basis,a refined finite element(FE)model of a precast concrete barrier was developed.The impact locations,impact load,boundary constraints,and reinforcement types were used as variables and the dynamic response of the precast concrete barrier was systematically analyzed under 36 working conditions.The simulated results indicated that the damage state of the concrete barrier and the stress of the reinforcing bars were accurately and quantitatively reflected.According to the computed results,some suggestions were put forward for selecting the appropriate reinforcement type of the precast concrete barrier and the connection between the superstructure and foundation.

An Investigation of Optimal Machine Learning Methods for the Prediction of ROTI

The rate of the total electron content(TEC)change index(ROTI)can be regarded as an effective indicator of the level of ionospheric scintillation,in particular in low and high latitude regions.An accurate prediction of the ROTI is essential to reduce the impact of the ionospheric scintillation on earth observation systems,such as the global navigation satellite systems.However,it is difficult to predict the ROTI with high accuracy because of the complexity of the ionosphere.In this study,advanced machine learning methods have been investigated for ROTI prediction over a station at high-latitude in Canada.These methods are used to predict the ROTI in the next 5 minutes using the data derived from the past 15 minutes at the same location.Experimental results show that the method of the bidirectional gated recurrent unit network(BGRU)outperforms the other six approaches tested in the research.It is also confirmed that the RMSEs of the predicted ROTI using the BGRU method in all four seasons of 2017 are less than 0.05 TECU/min.It is demonstrated that the BGRU method exhibits a high level of robustness in dealing with abrupt solar activities.

Real-time GNSS precise point positioning with smartphones for vehicle navigation

The availability of raw Global Navigation Satellite System(GNSS)measurements from Android smart devices gives new possibilities for precise positioning solutions,e.g.,Precise Point Positioning(PPP).However,the accuracy of the PPP with smart devices currently is a few meters due to the poor quality of the raw GNSS measurements in a kinematic scenario and in urban environments,particularly when the smart devices are placed inside vehicles.To promote the application of GNSS PPP for land vehicle navigation with smart devices,this contribution studies the real-time PPP with smartphones.For data quality analysis and positioning performance validation,two vehicle-based kinematic positioning tests were carried out using two Huawei Mate30 smartphones and two Huawei P40 smartphones with different installation modes:the vehicle-roof mode with smartphones mounted on the top roof outside the vehicle,and the dashboard mode with smartphones stabilized on the dashboard inside the vehicle.To realize high accuracy positioning,we proposed a real-time smartphone PPP method with the data processing strategies adapted for smart devices.Positioning results show that the real-time PPP can achieve the horizontal positioning accuracy of about 1–1.5 m in terms of root-mean-square and better than 2.5 m at the 95th percentile for the vehicle-based kinematic positioning with the experimental smartphones mounted on the dashboard inside the vehicle,which is the real scenario in vehicle navigation.

Status of CAS global ionospheric maps after the maximum of solar cycle 24

As a new Ionosphere Associate Analysis Center(IAAC)of the International GNSS Service(IGS),Chinese Academy of Sciences(CAS)started the routine computation of the real-time,rapid,and final Global Ionospheric Maps(GIMs)in 2015.The method for the generation of CAS rapid and final GIMs and recent updates are presented in the paper.The quality of CAS post-processed GIMs is assessed during 2015-2018 after the maximum of solar cycle 24.To perform an independent and fair assessment,Jason-2/3 Vertical Total Electron Contents(VTEC)are first used as the references over the ocean.GPS differential Slant TECs(dSTEC)generated from 55 Multi-GNSS Experimental(MGEX)stations of the IGS are also employed,which provides a complementing way to evaluate the ability of electron content models to reproduce the spatial and temporal gradients in the ionosphere.During the test period,Jet Propulsion Laboratory(JPL)GIMs present significantly positive deviations compared to the Jason VTEC and GPS dSTEC.Technical University of Catalonia(UPC)rapid GIM UQRG exhibits the best performance in both Jason VTEC and GPS dSTEC analysis.The CAS GIMs show comparable performance with the results of the first four IAACs of the IGS.As expected,the poor performance of all GIMs is in equatorial regions and the high latitudes of the southern hemisphere.The consideration of generating multi-layer or three-dimensional ionospheric maps is emphasized to mitigate the inadequacy of ionospheric single-layer assumption in the presence of pronounced latitudinal gradients.The use of ionospheric observations from the new GNSS constellations and other space-or ground-based observation techniques is also suggested in the generation of future GIMs,given the sparse GPS/GLONASS stations in the southern hemisphere.