TEC and Instrumental Bias Estimation of GAGAN Station Using Kalman Filter and SCORE Algorithm

The standalone Global Positioning System (GPS) does not meet the higher accuracy requirements needed for approach and landing phase of an aircraft. To meet the Category-I Precision Approach (CAT-I PA) requirements of civil aviation, satellite based augmentation system (SBAS) has been planned by various countries including USA, Europe, Japan and India. The Indian SBAS is named as GPS Aided Geo Augmented Navigation (GAGAN). The GAGAN network consists of several dual frequency GPS receivers located at various airports around the Indian subcontinent. The ionospheric delay, which is a function of the total electron content (TEC), is one of the main sources of error affecting GPS/SBAS accuracy. A dual frequency GPS receiver can be used to estimate the TEC. However, line-of-sight TEC derived from dual frequency GPS data is corrupted by the instrumental biases of the GPS receiver and satellites. The estimation of receiver instrumental bias is particularly important for obtaining accurate estimates of ionospheric delay. In this paper, two prominent techniques based on Kalman filter and Self-Calibration Of pseudo Range Error (SCORE) algorithm are used for estimation of instrumental biases. The estimated instrumental bias and TEC results for the GPS Aided Geo Augmented Navigation (GAGAN) station at Hyderabad (78.47°E, 17.45°N), India are presented.

The influence of ionospheric thin shell height on TEC retrieval from GPS observation

We investigate the influence of assumed height for the thin shell ionosphere model on the Total Electron Content（TEC） derived from a small scale Global Positioning System（GPS） network. TEC and instrumental bias are determined by applying a grid-based algorithm to the data on several geomagnetically quiet days covering a 10 month period in 2006. Comparisons of TEC and instrumental bias are made among assumed heights from 250 km to 700 km with an interval of 10 km. While the TEC variations with time follow the same trend, TEC tends to increase with the height of the thin shell. The difference in TEC between heights 250 km and 700 km can be as large as～8 TECU in both daytime and nighttime. The times at which the TEC reaches its peak or valley do not vary much with the assumed heights. The instrumental biases, especially bias from the satellite, can vary irregularly with assumed height. Several satellites show a large deviation of～3 ns for heights larger than 550 km. The goodness of fit for different assumed heights is also examined. The data can be generally well-fitted for heights from 350 km to 700 km. A large deviation happens at heights lower than 350 km. Using the grid-based algorithm, there is no consensus on assumed height as related to data fitting. A thin shell height in the range 350-500 km can be a reasonable compromise between data fitting and peak height of the ionosphere.