Gaussian Random Process and Its Application for Detecting the Ionospheric Disturbances Using GPS

H. Zhang, J. Wang, W. Y. Zhu, C. Huang

School of Surveying and Spatial Information Systems, University of New South Wales, Sydney, Australia.
Shanghai Astronomical Observatory, Chinese Academy of Sciences, 80# Nandan R.d, Shanghai, China.
Shanghai Astronomical Observatory, Chinese Academy of Sciences, 80# Nandan R.d, Shanghai, China Graduate School of Chinese Academy of Sciences, Beijing 100039, China.

DOI:                 

Abstract

Usually, ionospheric Total Electron Content (TEC) variation with time can be viewed as a stationary random process under quiet conditions. However, sudden events of the Sun and the Earth such as solar flare and sudden commencement of geomagnetic storms may induce the disturbances of the ionosphere, so that the stationary random process is broken; the statistical model parameters change much. Based on this fact, here we make use of the time series of TEC and the autocovariance function of the stationary process to construct independent identical distribution Gauss sample so that the χ 2 test can be used to detect the abnormity hidden in the sequence. In addition, GPS data from several IGS sites in China during the severe solar flare occurred on 14th July, 2000 are used to verify the method. The results indicate that the disturbances caused by the solar flare can be effectively detected.

Keywords

GPS, Total Electron Content, Gaussian Random Process, Ionospheric disturbances

Conflicts of Interest

The authors declare no conflicts of interest.

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