The positioning service aided by low Earth orbit(LEO)mega-constellations has become a hot topic in recent years.To achieve precise positioning,accuracy of the LEO clocks is important for single-receiver users.To bridg...The positioning service aided by low Earth orbit(LEO)mega-constellations has become a hot topic in recent years.To achieve precise positioning,accuracy of the LEO clocks is important for single-receiver users.To bridge the gap between the applicable time of the clock products and the time of positioning,the precise LEO clocks need to be predicted over a certain period depending on the sampling interval of the clock products.This study discusses the prediction errors for periods from 10 s to 1 h for two typical LEO clock types,i.e.the ultra-stable oscillator(USO)and the oven-controlled crystal oscillator(OCXO).The prediction is based on GNSS-determined precise clock estimates,where the clock stability is related to the GNSS estimation errors,the behaviors of the oscillators themselves,the systematic effects related to the environment and the relativistic effects,and the stability of the time reference.Based on real data analysis,LEO clocks of the two different types are simulated under different conditions,and a prediction model considering the systematic effects is proposed.Compared to a simple polynomial fitting model usually applied,the proposed model can significantly reduce the prediction errors,i.e.by about 40%-70%in simulations and about 5%-30%for real data containing different miss-modeled effects.For both clock types,short-term prediction of 1 min would result in a root mean square error(RMSE)of a few centimeters when using a very stable time reference.The RMSE amounts to about 0.1 m,when a typical real-time time reference of the national center for space studies(CNES)real-time clocks was used.For long-term prediction of 1 h,the RMSE could range from below 1 m to a few meters for the USOs,depending on the complexity of the miss-modeled effects.For OCXOs,the 1 h prediction could lead to larger errors with an RMSE of about 10 m.展开更多
With the Gravity Recovery and Climate Experiment {GRACE） mission as the prime example, an overview is given on the management and processing of Level IA data of a low-low satellite to satellite tracking mission. To i...With the Gravity Recovery and Climate Experiment {GRACE） mission as the prime example, an overview is given on the management and processing of Level IA data of a low-low satellite to satellite tracking mission. To illustrate the underlying principle and algorithm, a detailed study is made on the K-band ranging （KBR） assembly, which includes the measurement principles, modeling of noises, the generation of Level 1A data from that of Level 0 as well as Level IA to Level IB data processing.展开更多
基金the Australian Research Council[Project number DP 190102444]Tracking Formation-Flying of Nanosatellites Using Inter-Satellite Links.
文摘The positioning service aided by low Earth orbit(LEO)mega-constellations has become a hot topic in recent years.To achieve precise positioning,accuracy of the LEO clocks is important for single-receiver users.To bridge the gap between the applicable time of the clock products and the time of positioning,the precise LEO clocks need to be predicted over a certain period depending on the sampling interval of the clock products.This study discusses the prediction errors for periods from 10 s to 1 h for two typical LEO clock types,i.e.the ultra-stable oscillator(USO)and the oven-controlled crystal oscillator(OCXO).The prediction is based on GNSS-determined precise clock estimates,where the clock stability is related to the GNSS estimation errors,the behaviors of the oscillators themselves,the systematic effects related to the environment and the relativistic effects,and the stability of the time reference.Based on real data analysis,LEO clocks of the two different types are simulated under different conditions,and a prediction model considering the systematic effects is proposed.Compared to a simple polynomial fitting model usually applied,the proposed model can significantly reduce the prediction errors,i.e.by about 40%-70%in simulations and about 5%-30%for real data containing different miss-modeled effects.For both clock types,short-term prediction of 1 min would result in a root mean square error(RMSE)of a few centimeters when using a very stable time reference.The RMSE amounts to about 0.1 m,when a typical real-time time reference of the national center for space studies(CNES)real-time clocks was used.For long-term prediction of 1 h,the RMSE could range from below 1 m to a few meters for the USOs,depending on the complexity of the miss-modeled effects.For OCXOs,the 1 h prediction could lead to larger errors with an RMSE of about 10 m.
基金the project entitled"Advanced Gravity Measurement in Space"supported by the National Space Science Center,Chinese Academy of Sciences Profs.Wenrui Hu and Houze Xu's effort to promote satellite gravity research in China motivated the feasibility study in the first placeSupport from National Natural Science Foundation of China(11305255,11171329 and 41404019)funding from State Key Laboratory of Geodesy and Earth's Dynamics,Institute of Geodesy and Geophysics,Chinese Academy of Sciences(SKLGED2013-3-8-E)are acknowledged
文摘With the Gravity Recovery and Climate Experiment {GRACE） mission as the prime example, an overview is given on the management and processing of Level IA data of a low-low satellite to satellite tracking mission. To illustrate the underlying principle and algorithm, a detailed study is made on the K-band ranging （KBR） assembly, which includes the measurement principles, modeling of noises, the generation of Level 1A data from that of Level 0 as well as Level IA to Level IB data processing.
