MA Jun, CAO Cheng-du, JIANG Wei-ping, ZHOU Lü. Elimination of Colored Noise in GNSS Station Coordinate Time Series by Using Wavelet Packet Coefficient Information Entropy[J]. Geomatics and Information Science of Wuhan University, 2021, 46(9): 1309-1317. DOI: 10.13203/j.whugis20190353
Citation: MA Jun, CAO Cheng-du, JIANG Wei-ping, ZHOU Lü. Elimination of Colored Noise in GNSS Station Coordinate Time Series by Using Wavelet Packet Coefficient Information Entropy[J]. Geomatics and Information Science of Wuhan University, 2021, 46(9): 1309-1317. DOI: 10.13203/j.whugis20190353

Elimination of Colored Noise in GNSS Station Coordinate Time Series by Using Wavelet Packet Coefficient Information Entropy

  •   Objectives  The global navigation satellite system(GNSS) coordinate time series can be used to analyze the motion of GNSS station, and the colored noise in coordinate time series affects the estimation accuracy of the motion parameters. Therefore, in order to improve the reliability of the motion analysis, it is necessary to take effective measures to eliminate the colored noise.
      Methods  This paper proposes a method to eliminate colored noise by combining wavelet packet transform and information entropy theory. First, the simulation time series containing flicker noise is estimated to verify the estimation accuracy of the flicker noise. Then, discrete wavelet transform and wavelet packet transform are respectively carried out on the residual series of the simulation time series, and the flicker noise is eliminated by using information entropy.On this basis, the denoising effects of these two methods are compared. Finally, the coordinate time series at KMIN station is used as the measured data to further verify the denoising effect of wavelet packet coefficient information entropy.
      Results  The experimental results show that the power spectrum and the time series of colored noise eliminated by using wavelet packet coefficient information entropy are in good agreement with the original colored noise.
      Conclusions  The proposed method can effectively eliminate colored noise in the residual series and only retain white noise.
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