Low-orbiting satellites have the advantages of rapid geometric configuration changes and strong ground receiving signals, which have a significant effect on accelerating the convergence speed of precise single-point positioning. During the operation of the satellite, it is affected by many complex perturbation forces such as sunlight pressure, atmospheric resistance and empirical force, and its orbital changes are complex. At the same time, due to cost and weight constraints, high-precision atomic clocks are generally not equipped, and the long-term stability performance is poor. The accuracy of satellite orbit and clock error estimation has become the most important source of error affecting precision single-point positioning services. Therefore, it is necessary to realize the high-precision calculation of the low-orbit satellite orbit and clock error in real time. Estimating the solar pressure, atmospheric resistance and empirical power of low-orbit satellites requires a huge amount of observational data to participate in the calculation. This paper proposes a method to determine and predict the high-precision orbits and clock errors of navigation satellites and low-orbit satellites on the monitoring data of medium-high orbit satellites by global stations and low-orbit satellites, and use clock-error reduction algorithms to speed up the solution. Based on the data of IGS, the performance analysis of orbit and clock error estimation was carried out, and the estimation and forecast accuracy were obtained. On this basis, the simulation and analysis of the influence of orbit error and clock error error on the performance of precision single-point positioning. The methods and analysis results presented in this paper can provide a basis for the design of low-orbit navigation enhancement systems.


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    Title :

    Analysis on the Accuracy of LEO Satellite Orbit and Clock Error Estimation and Its Influence on PPP Performance


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Yang, Changfeng (editor) / Xie, Jun (editor) / Nie, Xin (author) / Ma, Fujian (author) / Zhao, Xinglong (author)


    Publication date :

    2022-05-05


    Size :

    13 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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