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Spectral analysis for GNSS coordinate time series using chirp fourier transform

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Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Spectral analysis for global navigation satellite system (GNSS) coordinate time series provides a principal tool to understand the intrinsic mechanism that affects tectonic movements. Spectral analysis methods such as the fast Fourier transform, Lomb–Scargle spectrum, evolutionary power spectrum, wavelet power spectrum, etc. are used to find periodic characteristics in time series. Among spectral analysis methods, the chirp Fourier transform (CFT) with less stringent requirements is tested with synthetic and actual GNSS coordinate time series, which proves the accuracy and efficiency of the method. With the length of series only limited to even numbers, CFT provides a convenient tool for windowed spectral analysis. The results of ideal synthetic data prove CFT accurate and efficient, while the results of actual data show that CFT is usable to derive periodic information from GNSS coordinate time series.
Czasopismo
Rocznik
Strony
1111--1118
Opis fizyczny
Bibliogr. 17 poz.
Twórcy
autor
  • The First Crustal Monitoring and Application Center, China Earthquake Administration, Tianjin, China
autor
  • The First Crustal Monitoring and Application Center, China Earthquake Administration, Tianjin, China
autor
  • The First Crustal Monitoring and Application Center, China Earthquake Administration, Tianjin, China
autor
  • Tianjin Normal University Jingu College, Tianjin, China
Bibliografia
  • 1. Alvaro S-G (2011) Correlated errors in GPS position time series: implications for velocity estimates. J Geophys Res 116(B1):384–398
  • 2. Baldysz Z, Nykiel G, Figurski M, Szafranek K, Krosczynski K (2015) Investigation of the 16-year and 18-year ZTD time series derived from GPS data processing. Acta Geophys 63(4):1103–1125
  • 3. Blewitt G, Lavallée D, Clarke P, Nurutdinov K (2001) A new global mode of earth deformation: seasonal cycle detected. Science 294(5550):2342–2345
  • 4. Bogusz J, Klos A (2016) On the significance of periodic signals in noise analysis of GPS station coordinates time series. GPS Solut 20(4):655–664
  • 5. Bos MS, Fernandes RMS, Williams SDP, Bastos L (2013) Fast error analysis of continuous GNSS observations with missing data. J Geod 87(4):351–360
  • 6. Goudarzi MA, Cocard M, Santerre R, Woldai T (2013) GPS interactive time series analysis software. GPS Solut 17(4):595–603
  • 7. Kasdin NJ (1995) Discrete simulation of colored noise and stochastic processes and 1/fapower law noise generation. Proc IEEE 83(5):802–827
  • 8. King R, Bock Y (2000) Documentation for the GAMIT GPS analysis software, release 9.9. Mass. Inst. of Technol., Cambridge
  • 9. Mao A, Harrison CGA, Dixon TH (1999) Noise in GPS coordinate time series. J Geophys Res 104(B2):2797–2816
  • 10. Meyer-Bäse U, Natarajan H, Castillo E, Garcia A (2006) Faster than the FFT: the chirp-z RAG-n discrete fast Fourier transform. Frequenz 60(7–8):147–151
  • 11. Monro DM, Branch JL (1977) Algorithm AS 117: the chirp discrete Fourier transform of general length. J R Stat Soc Ser C (Appl Stat) 26(3):351–361
  • 12. Nikolaidis R (2002) Observation of geodetic and seismic deformation with the global positioning system. Thesis (Ph.D.), University of California, San Diego
  • 13. Ray J, Altamimi Z, Collilieux X, van Dam T (2008) Anomalous harmonics in the spectra of GPS position estimates. GPS Solut 12(1):55–64
  • 14. Tian Y (2011) iGPS: IDL tool package for GPS position time series analysis. GPS Solut 15(3):299–303
  • 15. Wessel P, Smith WHF (1998) New, improved version of the generic mapping tools released. EOS Trans AGU 79:579
  • 16. Williams SDP (2008) CATS: GPS coordinate time series analysis software. GPS Solut 12(2):147–153
  • 17. Williams SDP, Bock Y, Fang P, Jamason P, Nikolaidis RM, Prawirodirdjo L, Miller M, Johnson DJ (2004) Error analysis of continuous GPS position time series. J Geophys Res 109(B3):B03412
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8c4dc10c-8fb0-4f3a-b6c7-623d16f31b07
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