Abstract
Observable-specific bias (OSB) parameterization allows observation biases belonging to various signal types to be flexibly addressed in the estimation of ionosphere and global navigation satellite system (GNSS) clock products. In this contribution, multi-GNSS OSBs are generated by two different methods. With regard to the first method, geometry-free (GF) linear combinations of the pseudorange and carrier-phase observations of a global multi-GNSS receiver network are formed for the extraction of OSB observables, and global ionospheric maps (GIMs) are employed to correct ionospheric path delays. Concerning the second method, satellite and receiver OSBs are converted directly from external differential code bias (DCB) products. Two assumptions are employed in the two methods to distinguish satellite- and receiver-specific OSB parameters. The first assumption is a zero-mean condition for each satellite OSB type and GNSS signal. The second assumption involves ionosphere-free (IF) linear combination signal constraints for satellites and receivers between two signals, which are compatible with the International GNSS Service (IGS) clock product. Agreement between the multi-GNSS satellite OSBs estimated by the two methods and those from the Chinese Academy of Sciences (CAS) is shown at levels of 0.15 ns and 0.1 ns, respectively. The results from observations spanning 6 months show that the multi-GNSS OSB estimates for signals in the same frequency bands may have very similar code bias characteristics, and the receiver OSB estimates present larger standard deviations (STDs) than the satellite OSB estimates. Additionally, the variations in the receiver OSB estimates are shown to be related to the types of receivers and antennas and the firmware version. The results also indicate that the root mean square (RMS) of the differences between the OSBs estimated based on the CAS- and German Aerospace Center (DLR)-provided DCB products are 0.32 ns for the global positioning system (GPS), 0.45 ns for the BeiDou navigation satellite system (BDS), 0.39 ns for GLONASS and 0.22 ns for Galileo.
Highlights
When processing pseudorange observations from the global navigation satellite system (GNSS), the code bias generated by the time difference between the signal emission or reception time and the related satellite or receiver clock reading must be carefully addressed [1]
Code biases are commonly handled as differential code biases (DCBs) inherited by both satellites and receivers in ionospheric estimations based on geometry-free (GF) linear combinations of dual-frequency GNSS observations [2,3,4]
Considering the DCB estimates as pseudomeasurements, the satellite and receiver observable-specific bias (OSB) can be estimated based on the following equations:
Summary
When processing pseudorange observations from the global navigation satellite system (GNSS), the code bias generated by the time difference between the signal emission or reception time and the related satellite or receiver clock reading must be carefully addressed [1]. Code biases are commonly handled as differential code biases (DCBs) inherited by both satellites and receivers in ionospheric estimations based on geometry-free (GF) linear combinations of dual-frequency GNSS observations [2,3,4]. In the estimation of GNSS clock products, code biases are commonly treated as ionosphere-free (IF) linear combinations of signal biases [5]. DCB-related products have been provided by several agencies for the proper processing of different observables and frequencies in ionospheric delay modeling and satellite clock corrections. GPS and GLONASS DCBs are contained in the global ionospheric maps (GIMs) provided by the Ionosphere Associate
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
