Resolving the Regional Ionospheric Grid Model by Applying Kalman Filter

Abstract

Ionospheric is the largest error source in the high-precision navigation and positioning. However, single-frequency users can only get the correction by broadcast of the ionosphere models. In this paper, advantages and disadvantages of several kinds of current models are compared, and finally we choose the regional grid modeling. Based on GPS data of “Crustal Movement Observation Network of China” (CMONOC), we extract ionospheric delay from leveled carrier phase observations and take VTEC of the grid points and DCB of receivers as parameters, then describe each state variable with random walk model, thus, setting up the regional ionospheric grid model using the Kalman filter estimation epoch by epoch, which gained good results. Taking global ionospheric maps (GIM) as reference, their variations characteristics of VTEC (vertical total electron content)were consistent. The inner precision of the model ranging from 1 to 3 TECU was detected, and the RMS were about 2.5 TEC and residuals were around 3 TECU. Besides, variations of receiver hardware delay within 2 TECU were relatively smooth. Compared with the regional stations’ receiver DCB isolated from the original observation using satellite DCB and spherical harmonic coefficients, the mean differences for a week were all within 2 ns. In addition, the results showed that less stations around grid leading to lower precision of VTEC because of shortage of the observations, and thus the greater the receiver DCB error was.