With the continued development of multiple Global Navigation Satellite Systems(GNSS)and the emergence of various frequencies,UnDifferenced and UnCombined(UDUC)data processing has become an increasingly attractive opti...With the continued development of multiple Global Navigation Satellite Systems(GNSS)and the emergence of various frequencies,UnDifferenced and UnCombined(UDUC)data processing has become an increasingly attractive option.In this contribution,we provide an overview of the current status of UDUC GNSS data processing activities in China.These activities encompass the formulation of Precise Point Positioning(PPP)models and PPP-Real-Time Kinematic(PPP-RTK)models for processing single-station and multi-station GNSS data,respectively.Regarding single-station data processing,we discuss the advancements in PPP models,particularly the extension from a single system to multiple systems,and from dual frequencies to single and multiple frequencies.Additionally,we introduce the modified PPP model,which accounts for the time variation of receiver code biases,a departure from the conventional PPP model that typically assumes these biases to be time-constant.In the realm of multi-station PPP-RTK data processing,we introduce the ionosphere-weighted PPP-RTK model,which enhances the model strength by considering the spatial correlation of ionospheric delays.We also review the phase-only PPP-RTK model,designed to mitigate the impact of unmodelled code-related errors.Furthermore,we explore GLONASS PPP-RTK,achieved through the application of the integer-estimable model.For large-scale network data processing,we introduce the all-in-view PPP-RTK model,which alleviates the strict common-view requirement at all receivers.Moreover,we present the decentralized PPP-RTK data processing strategy,designed to improve computational efficiency.Overall,this work highlights the various advancements in UDUC GNSS data processing,providing insights into the state-of-the-art techniques employed in China to achieve precise GNSS applications.展开更多
The method of integrated data processing for GPS and INS(inertial navigation system) field test over the Rocky Mountains using the adaptive Kalman filtering technique is presented. On the basis of the known GPS output...The method of integrated data processing for GPS and INS(inertial navigation system) field test over the Rocky Mountains using the adaptive Kalman filtering technique is presented. On the basis of the known GPS outputs and the offset of GPS and INS, state equations and observations are designed to perform the calculation and improve the navigation accuracy. An example shows that with the method the reliable navigation parameters have been obtained.展开更多
This study introduces some innovations in the data processing algorithm for Chinese FY meteorological satellites. Issues about satellite image navigation, radiation calibration, and data assimilation are discussed. A...This study introduces some innovations in the data processing algorithm for Chinese FY meteorological satellites. Issues about satellite image navigation, radiation calibration, and data assimilation are discussed. A time series of the earth＇s disk center-line count provides information on the orientation of the satellite spin axis. With this information, the altitude parameters of the satellite and then the earth disk location in the south-north direction may be solved. In each spin cycle, the satellite views the sun and the earth. Given the satellite position and altitude, the angle （β） subtended at the satellite by the sun and the earth can be calculated and predicted. Thus, the earth＇s disk location in the east-west direction is fixed. Based on this principle, we derived an automatic image navigation algorithm for FY2 geosynchronous meteorological satellites with an accuracy approaching pixel level. The FY2 meteorological satellite traveling in a geostationary orbit suffers a large amount of radiation from the sun. The radiation varies on both diurnal and annual scales, which causes radiation responses in the thermal infrared （IR） bands wherein the wavelengths greater than 3.5 μm vibrate periodically on scales of hours to years. These vibrations must be precisely calibrated. First, based on the accurate estimation of the radiant contribution from the front-optics, the variation characteristics of the calibration parameters are obtained on a temporal scale of hours from the space-borne inner-blackbody （IBB） measurement results. Second, the in-orbit measured radiation of the lunar surface is referenced and utilized to correct the sys- tematic bias of the IBB calibration from daily to annual scales. By using such algorithms, we achieved a calibration accuracy of the FY2 satellite＇s IR imagery of less than 1 K. The on-orbit satellite instrument parameters play an important role in data quality; however, they may be mis-measured due to limitations in the measurement conditions or may be changed due to the space environment after launch. A satellite instrument parameters on-orbit optimizer （SIPOn-Opt） for a polar orbit meteorological satellite was developed to optimize the true state of the instrument parameters on-orbit with regard to the observation constraints. When applying the SIPOn-Opt to FY3 sounding instruments, the FY3 data quality was much improved, compared to its European and the U.S. polar orbit meteorological satellite counterparts, leading to improved forecast skill of numerical weather prediction.展开更多
基金National Natural Science Foundation of China(No.42022025)。
文摘With the continued development of multiple Global Navigation Satellite Systems(GNSS)and the emergence of various frequencies,UnDifferenced and UnCombined(UDUC)data processing has become an increasingly attractive option.In this contribution,we provide an overview of the current status of UDUC GNSS data processing activities in China.These activities encompass the formulation of Precise Point Positioning(PPP)models and PPP-Real-Time Kinematic(PPP-RTK)models for processing single-station and multi-station GNSS data,respectively.Regarding single-station data processing,we discuss the advancements in PPP models,particularly the extension from a single system to multiple systems,and from dual frequencies to single and multiple frequencies.Additionally,we introduce the modified PPP model,which accounts for the time variation of receiver code biases,a departure from the conventional PPP model that typically assumes these biases to be time-constant.In the realm of multi-station PPP-RTK data processing,we introduce the ionosphere-weighted PPP-RTK model,which enhances the model strength by considering the spatial correlation of ionospheric delays.We also review the phase-only PPP-RTK model,designed to mitigate the impact of unmodelled code-related errors.Furthermore,we explore GLONASS PPP-RTK,achieved through the application of the integer-estimable model.For large-scale network data processing,we introduce the all-in-view PPP-RTK model,which alleviates the strict common-view requirement at all receivers.Moreover,we present the decentralized PPP-RTK data processing strategy,designed to improve computational efficiency.Overall,this work highlights the various advancements in UDUC GNSS data processing,providing insights into the state-of-the-art techniques employed in China to achieve precise GNSS applications.
基金Supported by the Scientific Research Foundation for ROCS,SEMJiangxi Education Bureau Project(No.200525) .
文摘The method of integrated data processing for GPS and INS(inertial navigation system) field test over the Rocky Mountains using the adaptive Kalman filtering technique is presented. On the basis of the known GPS outputs and the offset of GPS and INS, state equations and observations are designed to perform the calculation and improve the navigation accuracy. An example shows that with the method the reliable navigation parameters have been obtained.
基金Supported by the National Natural Science Foundation of China(40275007,41275036,40971200,41075019,41275034,91338203,and 40705037)China Meteorological Administration Special Public Welfare Research Fund(GYHY201206002)+1 种基金Ministry of Finance(201306001)Ministry of Science and Technology of China(863-2003AA133050 and 2012AA120903)
文摘This study introduces some innovations in the data processing algorithm for Chinese FY meteorological satellites. Issues about satellite image navigation, radiation calibration, and data assimilation are discussed. A time series of the earth＇s disk center-line count provides information on the orientation of the satellite spin axis. With this information, the altitude parameters of the satellite and then the earth disk location in the south-north direction may be solved. In each spin cycle, the satellite views the sun and the earth. Given the satellite position and altitude, the angle （β） subtended at the satellite by the sun and the earth can be calculated and predicted. Thus, the earth＇s disk location in the east-west direction is fixed. Based on this principle, we derived an automatic image navigation algorithm for FY2 geosynchronous meteorological satellites with an accuracy approaching pixel level. The FY2 meteorological satellite traveling in a geostationary orbit suffers a large amount of radiation from the sun. The radiation varies on both diurnal and annual scales, which causes radiation responses in the thermal infrared （IR） bands wherein the wavelengths greater than 3.5 μm vibrate periodically on scales of hours to years. These vibrations must be precisely calibrated. First, based on the accurate estimation of the radiant contribution from the front-optics, the variation characteristics of the calibration parameters are obtained on a temporal scale of hours from the space-borne inner-blackbody （IBB） measurement results. Second, the in-orbit measured radiation of the lunar surface is referenced and utilized to correct the sys- tematic bias of the IBB calibration from daily to annual scales. By using such algorithms, we achieved a calibration accuracy of the FY2 satellite＇s IR imagery of less than 1 K. The on-orbit satellite instrument parameters play an important role in data quality; however, they may be mis-measured due to limitations in the measurement conditions or may be changed due to the space environment after launch. A satellite instrument parameters on-orbit optimizer （SIPOn-Opt） for a polar orbit meteorological satellite was developed to optimize the true state of the instrument parameters on-orbit with regard to the observation constraints. When applying the SIPOn-Opt to FY3 sounding instruments, the FY3 data quality was much improved, compared to its European and the U.S. polar orbit meteorological satellite counterparts, leading to improved forecast skill of numerical weather prediction.
