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EN
Single-frequency Global Navigation Satellite System (GNSS) users require an efcient ionospheric delay correction model for improving their positional accuracy. GPS satellite range signals undergo time delay through the inhomogeneous and dynamic state of the ionosphere. The ionospheric delay is inverse proportional to the signal frequency square due to the dispersive nature of the ionospheric medium. There is a need for aid regional ionospheric broadcast correction model that is necessary for low-latitude ionospheric conditions. In this paper, a reduced order adjusted spherical harmonics function (ROASHF) ionospheric broadcast correction model with order and degree 2 is proposed for the Indian region. A dense GPS receiver network of 14 GPS receivers over the Indian region is analyzed to derive nine ROASHF broadcast coefcients. The performance of the proposed ionospheric broadcast correction model is compared with Klobuchar, NeQuickG, BDS-2, CODEKlob, and CODEGIM TEC models during March and September equinox and June and December solstice days in 2015 and 2016. The mean root mean square error (RMSE) of ROASHF, Klobuchar, NeQuickG, BDS-2, CODEKlob, and CODEGIM TEC models is 7.13 TECU, 9.52 TECU, 15.52 TECU, 11.44 TECU, 13.47 TECU, and 11.97 TECU, respectively. The results demonstrated that the proposed ROASHF ionospheric broadcast model could better predict the ionospheric delays for single-frequency GNSS users. The proposed ionospheric broadcast model is suitable for the Indian regional navigation system known as Navigation with Indian Constellation (NavIC).
EN
Ephemerides are essential for the satellite positioning in Global Navigation Satellite Systems (GNSS) user receivers. Acquisition of navigation data and ephemeris parameters are difficult in remote areas as well as in challenging environments. Statistical orbit determination techniques can help to predict the orbital parameters in the absence of navigation data. The present study is a first step towards the solution for generating orbital parameters and predicting the satellite positions in the absence of navigation data for satellites in NavIC constellation. The orbit determination algorithm predicted the satellite position using single station navigation data. The perturbations affecting the satellite orbits in NavIC constellation were also studied and an algorithm using perturbation force models is proposed for the satellites in NavIC constellation. Extended Kalman Filter (EKF) was used to address the non-linear dynamics model of the perturbation forces and distance of the ground station from the centre of Earth was used as measurement to solve the measurement equation. The satellite orbits were predicted up to 1 hour using the single station navigation data. The root mean square error (RMSE) of 12.59 m and 13.03 m were observed for NavIC satellites in Geosynchronous and Geostationary orbits, respectively, after 1 hour. The Kolmogorov-Smirnov test used to assess the goodness of fit of the proposed EKF algorithm for orbit prediction was found to be significant at 1% level of significance.
EN
The ionospheric total electron content (TEC) plays a major role in the estimation of positional accuracy of satellite-based navigation systems. TEC disturbs the transmission of the signal transmitted from the satellite to receiver, which leads to range error. Hence, the prediction of VTEC can rectify the range errors in advance. Navigation with Indian Constellation (NavIC) is a navigational satellite system that gives position of a user and time information in India. NavIC receiver is installed at ACSCE, Bangalore, and it is utilized to estimate vertical total electron content (VTEC). In this paper, VTEC estimated from ACSCE station and VTEC obtained from IISC station, Bangalore, are compared and also ordinary kriging-based sur rogate model (OKSM) and cokriging-based surrogate model (COKSM) are developed for forecasting NavIC/GPS VTEC. In these models, input parameters comprise the time, Bt, SSN, Ap and F10.7. NavIC and GPS VTEC are predicted for quiet days, i.e. from 16/1/2018 to 26/1/2018 and from 7/8/2018 to 13/8/2018, by using previous one week of VTEC data, and input parameters belong to ACSCE (12.8914° N, 77.4657° E) and IISC (13.0219° N, 77.5671° E) stations, Bangalore. The VTEC prediction results from OKSM and COKSM are compared. It shows that OKSM results are comparatively better than COKSM. In order to validate our developed models, OKSM and COKSM prediction results are compared with the SWIF model during storm days. Based on the comparison, it is observed that RMSE of OKSM is 3.5202 TECU, COKSM gives RMSE as 4.7126 TECU, and the SWIF model’s RMSE is 4.6804. From the comparison results, it is evident that OKSM yields better prediction results than COKSM and SWIF. These results indicate that the proposed model will be useful for correcting range measurement data in advance.
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