It is of particular interest to retrieve the electron density distribution from Global Navigation Satellite System (GNSS) observations due to its high density and broad spatial-temporal coverage. There are several commonly used methods such as Computerized Ionospheric Tomography (CIT), Bayesian analysis and Kalman filter (Bust et al., 2001;Prol et al., 2021;Scherliess et al., 2004). However, different methods differ in many aspects including computational cost, data storage and management cost, compatibility for different kinds of observations and flexibility in practical applications.Several different techniques are developed to perform posterior analyses of the ionospheric electron density. One of the traditional techniques is CIT. CIT is a direct inversion technique that develops a two-dimensional electron density specification from a series of one-dimensional ionospheric observations and various minimization criteria (Kronschnabl et al., 1997;Raymund, 1995;Raymund et al., 1994). Similar work by other groups have led to the development of more advanced spatial analysis techniques. Howe et al. (1998) developed a Kalman filter method for ionospheric reconstruction based on spherical harmonics and Empirical Orthogonal Function describing the horizontal and vertical distribution, respectively. Manuel Hernández-Pajares et al. (1999, 2002)