Wavelet transform based kalman filtering algorithm for anti-sa effect

Yongliang Xiong, Dingfa Huang, Xiaoli Ding, Yongqi Chen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)


A new mathematical approach, wavelet transformation, is introduced for GPS data analysis. Based on its good features on both time-domain and frequency-domain, one can obtain a true time-frequency representation of a signal. The so-called mutiresolution analysis (MRA) will be used for data analysis, such as for the removal of noises, and the detection and rejection of gross errors from signal. In this paper the authors present a wavelet-based algorithm for the modeling and prediction of SA effect by combining time series analysis methods. A new self-adaptive Kalman filtering algorithm is presented for anti-SA. Some preliminary test results from experimental data are also summarized.
Original languageEnglish
Pages (from-to)165-169
Number of pages5
JournalGeographic Information Sciences
Issue number2
Publication statusPublished - 1 Dec 2000

ASJC Scopus subject areas

  • Computer Science Applications
  • General Earth and Planetary Sciences


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