Application of a novel data mining method based on wavelet analysis and neural network satellite clock bias prediction

  • Authors:

  • Chengjun Guo;Yunlong Teng

  • Affiliations:

  • University of Electronic Science and Technology of China, Research Institute of Electronic Science and Technology, Chengdu, China;University of Electronic Science and Technology of China, Research Institute of Electronic Science and Technology, Chengdu, China

  • Venue:
  • ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
  • Year:
  • 2011

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Abstract

A novel four-stage data mining method for clock bias prediction based on wavelet analysis and FONN (fuzzy optimization neural networks) is proposed. The basic ideas, prediction models and steps of clock bias prediction based on wavelet analysis and FONN are discussed respectively. And then, to validate the feasibility and validity of the proposed method, make a careful precision analysis for satellite clock bias prediction with the performance parameters of GPS satellite clock, and make comparison and analysis with Grey system model and neural network model. The results of simulation shows that the prediction precision of the novel four-stage model based on wavelet analysis and FONN is more better, can afford high precise satellite clock bias prediction for real-time GPS precise point positioning.