Receiver DCB analysis and calibration in geomagnetic storm-time using IGS products

References

• Afraimovich, E.L., et al., 2008. Global electron content: a new conception to track solar activity. Annales Geophysicae, 26, 335–344. doi: 10.5194/angeo-26-335-2008
   Web of Science ®Google Scholar
• Afraimovich, E.L., Astafyeva, E.I., and Zhivetiev, I.V., 2006. Solar activity and global electron conten. Doklady Earth Science, 409 (2), 921–924. doi:10.1134/S1028334X06060195.
   Google Scholar
• Arikan, F., et al., 2008. Estimation of single station interfrequency receiver bias using GPS-TEC. Radio Scinece, 43, 4. doi:10.1029/2007rs003785.
   Web of Science ®Google Scholar
• Azpilicueta, F., Brunini, C., and Radicella, S., 2006. Global ionospheric maps from GPS observations using modip latitude. Advances in Space Research, 38, 2324–2331. doi: 10.1016/j.asr.2005.07.069
   Web of Science ®Google Scholar
• Baker, D.N., Turner, N.E., and Pulkkinen, T.I., 2001. Energy transport and dissipation in the magnetosphere during geomagnetic storms. Journal of Atmospheric and Solar-Terrestrial Physics, 63 (5), 421–429. doi: 10.1016/S1364-6826(00)00169-3
   Web of Science ®Google Scholar
• Brunini, C., et al., 2010. GPS slant total electron content accuracy using single layer model under different geomagnetic regions and ionospheric conditions. Journal of Geodesy, 84, 293–304. doi:10.1007/s00190-010-0367-5.
   Web of Science ®Google Scholar
• Ciraolo, L., et al., 2007. Calibration errors on experimental slant total electron content (TEC) determined with GPS. Journal of Geodesy, 81 (2), 111–120. doi: 10.1007/s00190-006-0093-1
   Web of Science ®Google Scholar
• Conte, J., Azpilicueta, F., and Brunini, C., 2011. Accuracy assessment of the GPS-TEC calibration constants by means of a simulation technique. Journal of Geodesy, 85 (10), 1–8. doi:10.1007/s00190-011-0477-8.
   Web of Science ®Google Scholar
• Durmaz, M. and Karslioglu, M.O., 2015. Regional vertical total electron content (VTEC) modeling together with satellite and receiver differential code biases (DCBs) using semi-parametric multivariate adaptive regression B-splines (SP-BMARS). Journal of Geodesy, 89 (4), 347–360. doi:10.1007/s00190-014-0779-8.
   Web of Science ®Google Scholar
• Feltens, J., 2003. The international GPS service (IGS) ionosphere working group. Advances in Space Research, 31 (3), 635–644. doi: 10.1016/S0273-1177(03)00029-2
   Web of Science ®Google Scholar
• Hernández-Pajares, M., et al., 2009. The IGS VTEC maps: a reliable source of ionospheric information since 1998. Journal of Geodesy, 83 (3–4), 263–275. doi: 10.1007/s00190-008-0266-1
   Web of Science ®Google Scholar
• Hernández-Pajares, M., et al., 2011. The ionosphere: effects, GPS modeling and the benefits for space geodetic techniques. Journal of Geodesy, 85 (12), 887–907. doi: 10.1007/s00190-011-0508-5
   Web of Science ®Google Scholar
• Jin, R., Jin, S., and Feng, G., 2012. M_dcb: matlab code for estimating gnss satellite and receiver differential code biases. GPS Solutions, 16 (4), 541–548. doi: 10.1007/s10291-012-0279-3
   Web of Science ®Google Scholar
• Kao, S., et al., 2013. Factors affecting the estimation of GPS receiver instrumental biases. Survey Review, 45 (328), 59–67. doi: 10.1179/1752270612Y.0000000022
   Web of Science ®Google Scholar
• Keshin, M., 2011. A new algorithm for single receiver DCB estimation using IGS TEC maps. GPS Solut, 16 (3), 283–292. doi:10.1007/s10291-011-0230-z.
   Web of Science ®Google Scholar
• Klobuchar, J.A., 1987. Ionospheric time-delay algorithm for single-frequency GPS users. IEEE Transactions on Aerospace and Electronic Systems, 23, 325–331. doi: 10.1109/TAES.1987.310829
   Web of Science ®Google Scholar
• Komjathy, A., et al., 2005. Automated daily processing of more than 1000 ground-based GPS receivers for studying intense ionospheric storms. Radio Scinece, 40 (6), S6006. doi:10.1029/2005RS003279.
   Web of Science ®Google Scholar
• Leandro, R.F., Langley, R.B., and Santos, M.C. 2007. Estimation of P2-C2 biases by means of precise point positioning. In: Proceedings of the 63rd annual meeting of the Institute of Navigation, Cambridge, 23–25 April, 225–231.
   Google Scholar
• Li, Z., et al., 2012. Two-step method for the determination of the differential code biases of COMPASS satellites. Journal of Geodesy, 86 (11), 1059–1076. doi: 10.1007/s00190-012-0565-4
   Web of Science ®Google Scholar
• Li, Z., et al., 2015. SHPTS: towards a new method for generating precise global ionospheric TEC map based on spherical harmonic and generalized trigonometric series functions. Journal of Geodesy, 89 (4), 331–345. doi: 10.1007/s00190-014-0778-9
   Web of Science ®Google Scholar
• Li, M., et al., 2016a. Estimation and analysis of Galileo differential code biases. Journal of Geodesy, 91, 1–15.
   Web of Science ®Google Scholar
• Li, S., et al., 2016b. An empirical model for the ionospheric global electron content storm-time response. Acta Geophysica, 64, 253–269. doi: 10.1515/acgeo-2015-0067
   Web of Science ®Google Scholar
• Mannucci, A.J., Wilson, B.D., and Edwards, C.D. 1993. A new method for monitoring the earth’s ionospheric total electron content using the GPS global network. In: Proceeding of ION GPS-93. Salt Lake City: Institute of Navigation, 1323–1332.
   Google Scholar
• Meza, A., et al., 2005. Vertical total electron content and geomagnetic perturbations at mid- and sub-auroral southern latitudes during geomagnetic storms. Journal of Atmospheric and Solar-Terrestrial Physics, 67, 315–323. doi: 10.1016/j.jastp.2004.07.042
   Web of Science ®Google Scholar
• Montenbruck, O., et al., 2013. IGS-MGEX: preparing the ground for multi-constellation GNSS science. Inside GNSS, 9 (1), 42–49.
   Google Scholar
• Montenbruck, O., Hauschild, A., and Steigenberger, P., 2014. Differential code bias estimation using multi-GNSS observations and global ionosphere maps. Navigation, 61 (3), 191–201. doi: 10.1002/navi.64
   Web of Science ®Google Scholar
• Mylnikova, A.A., et al., 2015. Variability of GPS/GLONASS differential code biases[. Results in Physics, 5, 9–10. doi: 10.1016/j.rinp.2014.11.002
   Web of Science ®Google Scholar
• Palacios, J., et al., 2017. Defining scale thresholds for geomagnetic storms through statistics. Natural Hazards and Earth System Sciences Discussions, 2017, 1–19. doi:10.5194/nhess-2017-367.
   Google Scholar
• Sardon, E., Rius, A., and Zarraoa, N., 1994. Estimation of the transmitter and receiver differential biases and the ionospheric total electron content from Global Positioning System observations. Radio Science, 29 (3), 577–586. doi:10.1029/94RS00449.
   Web of Science ®Google Scholar
• She, C., Wan, W., and Xu, G., 2008. Climatological analysis and modeling of the ionospheric global electron content. Chinese Science Bulletin, 53 (2), 282–288. doi:10.1007/s11434-007-0519-z.
   Google Scholar
• Shi, C., et al., 2015. An enhanced algorithm to estimate BDS satellite’s differential code biases. Journal of Geodesy, 90 (2), 161–177. doi:10.1007/s00190-015-0863-8.
   Web of Science ®Google Scholar
• Xiong, N., Tang, C., and Li, X., 1999. Introduction to ionosphere physics. Wuhan: Wuhan University Press.
   Google Scholar
• Xue, J., Song, S., and Zhu, W., 2015. Estimation of differential code biases for Beidou navigation system using multi-GNSS observations: how stable are the differential satellite and receiver code biases. Journal of Geodesy, 90 (4), 309–312. doi:10.1007/s00190-015-0874-5.
   Web of Science ®Google Scholar
• Yasyukevich, Y.V., et al., 2015. Influence of GPS/GLONASS differential code biases on the determination accuracy of the absolute total electron content in the ionosphere. Geomagnetism & Aeronomy, 55 (6), 763–769. doi: 10.1134/S001679321506016X
   Web of Science ®Google Scholar
• Yuan, Y., et al., 2015. Monitoring the ionosphere based on the crustal movement observation network of China. Geodesy and Geodynamics, 6 (2), 73–80. doi: 10.1016/j.geog.2015.01.004
   Web of Science ®Google Scholar
• Yuan, Y., Huo, X., and Ou, J., 2007. Models and methods for precise determination of ionospheric delays using GPS. Prog Nat Sci, 17 (2), 187–196. doi:10.1080/10020070612331343245.
   Web of Science ®Google Scholar
• Zha, J., et al., 2019. Use of modified carrier-to-code leveling to analyze temperature dependence of multi-GNSS receiver DCB and to retrieve ionospheric TEC. GPS Soluttions, 23, 103. doi: 10.1007/s10291-019-0895-2
   Web of Science ®Google Scholar
• Zhang, B., et al., 2012. Extraction of line-of-sight ionospheric observables from GPS data using precise point positioning. Sci China Earth Sciences, 55 (11), 1919–1928. doi: 10.1007/s11430-012-4454-8
   Web of Science ®Google Scholar
• Zhang, B., et al., 2017b. Joint estimation of vertical total electron content (VTEC) and satellite differential code biases (SDCBS) using low-cost receivers. Journal of Geodesy, 92 (4), 401–413. doi: 10.1007/s00190-017-1071-5
   Web of Science ®Google Scholar
• Zhang, B., et al., 2018. A modified carrier-to-code leveling method for retrieving ionospheric observables and detecting short-term temporal variability of receiver differential code biases. Journal of Geodesy, 93 (1), 19–28. doi: 10.1007/s00190-018-1135-1
   Web of Science ®Google Scholar
• Zhang, B., Teunissen, P.J.G., and Yuan, Y., 2017a. On the short-term temporal variations of GNSS receiver differential phase biases. Journal of Geodesy, 91 (5), 563–572. doi: 10.1007/s00190-016-0983-9
   Web of Science ®Google Scholar
• Zhao, C., et al., 2018. Ionosphere sensing with a low-cost, single-frequency, multi-gnss receiver. IEEE Transactions on Geoscience and Remote Sensing, 57 (2), 1–12.
   Web of Science ®Google Scholar