In this article the time series data of GNSS station coordinates are analysed, using least-squares spectral analysis (LSSA). One type of LSSA, the method of estimating a frequency spectrum, is the Lomb–Scargle method. Because of the presence of discontinuities in GNSS measurements, we applied Lomb–Scargle model for detecting and characterizing periodicity. We analyzed time series data from the station SRJV (Sarajevo), for a period of about 20 years, and BEOG (Belgrade), for a period of about 5 years. The spectral analysis is used to determine quickly the predominant noise in the position time series. Analyzed spectral indices of noise (α) of GNSS coordinate time series of SRJV and BEOG are in the range of -1<α<1, and describe stationary stochastic process. Then we processed time-series data of two GNSS station coordinates during 5 earthquakes that occurred near SRVJ and BEOG stations and estimated spectral indices of power-law noise from postfit residuals after removing linear, annual and semi-annual variation in the position time series.
Key words: time series of GNSS coordinates; spectral analysis; Lomb-Scargle model; earthquake