Abstract
Dual frequency GPS receiver provides measurements at two frequencies, one at L1: 1575.42 MHz another at L2: 1227.60 MHz, over worldwide. Measurements of any GPS receiver are affected by instrument biases of satellite and receiver. Differential Code Bias (DCB) is the instrumental biases between two GNSS code observations at same or different frequencies. Knowledge of Precise Differential code bias for satellite and receiver end is essential for code based positioning, remote sensing of ionosphere, and other applications. This paper presents the estimation of DCB for GPS satellites and receiver along with the Local TEC estimation using spherical harmonic function. Measurements of single and multiple stations were taken for processing. DCB results obtained after the processing were compared with the results published by IGS Analysis center for validation, and found an agreement of ~±1 ns between them while processing with single station and ~ ±0.5 ns while processing with multiple receivers at different locations.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Schaer, S., Steigenberger, P.: Determination and use of GPS differential code bias values. In: IGS workshop, Darmstadt, Germany, May 8–11
Li, Z., Yuan, Y., Li, H., Ou, J., Huo, X.: Two-step method for the determination of the differential code biases of BDS satellites. J. Geodesy. 86, 1059–1076 (2012); Chen, W.-K.: Linear networks and systems (book style), pp. 123–135. Wadsworth, Belmont, CA (1993)
Zhang, Q., Zhan, Q.: Global Ionosphere mapping and differential code bias estimation during low and high solar activity periods with GIMAS software. Remote. Sens. 10, 705 (2018). https://doi.org/10.3390/rs10050705
Gun, F., Zhang, X., Wang, J.: Timing group delay and differential code bias corrections for BeiDou positioning. J Geod 89, 427–445 (2015)
Sanz, J., Juan, J.M.: GNSS measurements and their combinations. gAGE/UPC
Ammar, M., Aquino, M., Vadakke Veettiiil, S., Andreotti, M.: Estimation and analysis of multi-GNSS differential code biases using a hardware signal simulator. GPS Sol. (2018)
Sardonand, E., Zarraoa, N.: Estimation of total electron content using GPS data: how stable are the differential satellite and receiver instrumental biases? Radio Sci. 32(5), 1899–1910 (1997)
www.igs.org IGS. IONEX: The IONosphere Map Exchange format version 1. ESA/ESOC, Darmstadt, Germany, 25 Feb 1998
Silva, P.: Cycle slip detection and correction for precise point positioning
Montenbruck, O., Hauschild, A.: Differential code bias estimation using multi-GNSS observatios and global ionosphere maps. ION-ITM-2014, 27–29 Jan 2014, San Diego, USA
Zhang, D.H., Zhang, W., Li, Q., Shi, L.Q., Hao, Y.Q., Xiao, Z.: Accuracy analysis of the GPS instrumental bias estimated from observations in middle and low latitudes. Ann. Geophys. 28(8), 1571–1580 (2010)
Schaer, S.: Mapping and predicting the earth’s ionosphere using the global positioning system. In: Ph.D dissertation, Astronom. Institute of University Bern, Berne, Switzerland (1999)
Navigation Center: https://www.navcen.uscg.gov, GPS Almanacs
Acknowledgements
This work was carried out at ISTRAC/ISRO. Authors would like to be grateful to Director ISTRAC, Associate Director ISTRAC and entire IGSA/NSA team for their kind support, motivation, and encouragement. Authors would like to be thankful to IGS community for providing quality Data and precise products for GPS satellite.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Lingwal, Y., Singh, F.B., Ramakrishna, B.N. (2021). Estimation of Differential Code Bias and Local Ionospheric Mapping Using GPS Observations. In: Pandian, A.P., Palanisamy, R., Ntalianis, K. (eds) Proceedings of International Conference on Intelligent Computing, Information and Control Systems. Advances in Intelligent Systems and Computing, vol 1272. Springer, Singapore. https://doi.org/10.1007/978-981-15-8443-5_69
Download citation
DOI: https://doi.org/10.1007/978-981-15-8443-5_69
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-8442-8
Online ISBN: 978-981-15-8443-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)