Prediction of Navigation Satellite Clock Bias by Gaussian Process Regression View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015

AUTHORS

Yu Lei , Danning Zhao , Zhaopeng Hu , Hongbing Cai

ABSTRACT

Many studies have been carried out in the past for forecasting satellite clock bias utilizing models such as the grey model, linear model, quadratic polynomial model, etc., but the accuracy of these models has not met the requirements for real-time applications. One reason for the fact is that onboard atomic clocks can be easily affected by various factors such as environment and temperature and this leads to complex aspects like periodic and stochastic variations, which are not sufficiently described by conventional models. A hybrid prediction model is thus developed in this work in order to be used particularly in describing the stochastic variation behavior satisfactorily. The proposed hybrid prediction model for satellite clock bias combines the quadratic model plus harmonic model to overcome the linear and periodic effects, and Gaussian process regression (GPR), whose input is reconstructed by the delay coordinate embedding to access linear or nonlinear coupling characteristics. The simulation results have demonstrated that the prediction accuracy of the proposed model is better that of the IGS ultra-predicted (IGU-P) solutions at least on a daily basis. More... »

PAGES

411-423

References to SciGraph publications

  • 2014. A Novel Method for Navigation Satellite Clock Bias Prediction Considering Stochastic Variation Behavior in CHINA SATELLITE NAVIGATION CONFERENCE (CSNC) 2014 PROCEEDINGS: VOLUME III
  • 2013-10. Navigation Satellite Clock Error Prediction Based on Functional Network in NEURAL PROCESSING LETTERS
  • 2013. Research of Satellite Clock Error Prediction Based on RBF Neural Network and ARMA Model in CHINA SATELLITE NAVIGATION CONFERENCE (CSNC) 2013 PROCEEDINGS
  • 2013. A Hybrid Model for Navigation Satellite Clock Error Prediction in COMPUTATIONAL INTELLIGENCE
  • 2014-01. Real-time clock offset prediction with an improved model in GPS SOLUTIONS
  • 1981. Detecting strange attractors in turbulence in DYNAMICAL SYSTEMS AND TURBULENCE, WARWICK 1980
  • Book

    TITLE

    China Satellite Navigation Conference (CSNC) 2015 Proceedings: Volume III

    ISBN

    978-3-662-46631-5
    978-3-662-46632-2

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-662-46632-2_36

    DOI

    http://dx.doi.org/10.1007/978-3-662-46632-2_36

    DIMENSIONS

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    142 schema:name National Time Service Center, Chinese Academy of Sciences, Xi’an, 710600, China
    143 rdf:type schema:Organization
     




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