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Open AccessArticle

Estimation of GPS Differential Code Biases Based on Independent Reference Station and Recursive Filter

1
Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China
2
School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing 100049, China
3
School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
4
Jiangsu Engineering Center for Collaborative Navigation/Positioning and Smart Applications, Nanjing 210044, China
5
Institute of Solar-Terrestrial Physics, German Aerospace Center, Kalkhorstweg 53, 17235 Neustrelitz, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(6), 951; https://doi.org/10.3390/rs12060951
Received: 17 February 2020 / Revised: 9 March 2020 / Accepted: 13 March 2020 / Published: 16 March 2020
(This article belongs to the Special Issue Remote Sensing of Ionosphere Observation and Investigation)
The differential code bias (DCB) of the Global Navigation Satellite Systems (GNSS) receiver should be precisely corrected when conducting ionospheric remote sensing and precise point positioning. The DCBs can usually be estimated by the ground GNSS network based on the parameterization of the global ionosphere together with the global ionospheric map (GIM). In order to reduce the spatial-temporal complexities, various algorithms based on GIM and local ionospheric modeling are conducted, but rely on station selection. In this paper, we present a recursive method to estimate the DCBs of Global Positioning System (GPS) satellites based on a recursive filter and independent reference station selection procedure. The satellite and receiver DCBs are estimated once per local day and aligned with the DCB product provided by the Center for Orbit Determination in Europe (CODE). From the statistical analysis with CODE DCB products, the results show that the accuracy of GPS satellite DCB estimates obtained by the recursive method can reach about 0.10 ns under solar quiet condition. The influence of stations with bad performances on DCB estimation can be reduced through the independent iterative reference selection. The accuracy of local ionospheric modeling based on recursive filter is less than 2 Total Electron Content Unit (TECU) in the monthly median sense. The performance of the recursive method is also evaluated under different solar conditions and the results show that the local ionospheric modeling is sensitive to solar conditions. Moreover, the recursive method has the potential to be implemented in the near real-time DCB estimation and GNSS data quality check. View Full-Text
Keywords: global positioning system (GPS); differential code bias (DCB); recursive filter; reference station selection global positioning system (GPS); differential code bias (DCB); recursive filter; reference station selection
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MDPI and ACS Style

Yuan, L.; Jin, S.; Hoque, M. Estimation of GPS Differential Code Biases Based on Independent Reference Station and Recursive Filter. Remote Sens. 2020, 12, 951. https://doi.org/10.3390/rs12060951

AMA Style

Yuan L, Jin S, Hoque M. Estimation of GPS Differential Code Biases Based on Independent Reference Station and Recursive Filter. Remote Sensing. 2020; 12(6):951. https://doi.org/10.3390/rs12060951

Chicago/Turabian Style

Yuan, Liangliang; Jin, Shuanggen; Hoque, Mainul. 2020. "Estimation of GPS Differential Code Biases Based on Independent Reference Station and Recursive Filter" Remote Sens. 12, no. 6: 951. https://doi.org/10.3390/rs12060951

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