An experiment of predicting Total Electron Content (TEC) by fuzzy inference systems

O Akyilmaz,N Arslan

doi:10.1186/bf03352852

Abstract

Abstract The Total Electron Content (TEC) is predicted by fuzzy inference systems for various station-satellite pairs. GPS data from the GRAZ, HFLK, LINZ, MOPI and UZHL permanent stations are processed in order to obtain the vertical total electron content (VTEC) using differenced carrier-smoothed code observations. The quality of the VTEC prediction was studied on 9 and 11 September 2005 (DOY 252 and 254). The predictions were computed for 5, 10 and 15 min intervals. The mean accuracies of predictions are about 0.1, 0.2 and 0.3 TECU for these time intervals. More than 98% of the VTEC is successfully recovered with the proposed prediction method.

Highlights

Determining the Total Electron Content (TEC) from dual-frequency GPS observations has become an important application of GPS
1.2 1.4 1.7 1.8 2.0 2.2 ity series of vertical total electron content (VTEC) were computed for each satellite-station (a) pair by (4)
The input parameter for the prediction is VTEC, which can be computed from carrier smoothed-code observations

Summary

Introduction

Determining the Total Electron Content (TEC) from dual-frequency GPS observations has become an important application of GPS. The differential code biases (DCB) for the receivers and satellites must be taken into account when estimating the TEC (Sardon and Zarraoa, 1997; Rideout and Coster, 2006). These mapping functions often assume that the electrons are concentrated in a shell of infinitesimal thickness. Rideout and Coster (2006) extensively discussed mapping function errors, Ciraolo et al (2007) have studied the effects of the multipath on carrier-phase smoothed code observations using co-located receivers and intra-daily DCB variations for a zero-baseline experiment using single difference observations. Modeling of the Total Electron Content (TEC) The carrier-smoothed code observations can be written as

Tki cδk

GRAZ HFLK LINZ MOPI UZHL

LINZ MOPI

Findings

Conclusions