Successful Holding of the Academic Semin...

On the morning of 26 November 2025, the academic seminar “GNSS Atmospheric Remote Sensing: A Feasibility Study of Detecting Atmospheric Turbulence”, hosted by the Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, was successfully held in Meeting Room 206, Building 3, East Lake Campus. The seminar was chaired by Researcher Jianghui Geng, and Professor Zhiguo Deng of Liaoning Technical University served as the keynote speaker.First, Professor Zhiguo Deng delivered a presentation titled “GNSS Atmospheric Remote Sensing: A Feasibility Study of Detecting Atmospheric Turbulence.” At the beginning of the talk, Professor Deng explained the objectives of turbulence research, including supporting weather and atmospheric forecasting, aviation safety assurance, studies of atmospheric governance and pollutant dispersion, and wind-energy development. He then gave a detailed introduction to the principle by which GNSS electromagnetic signals experience refractive delay when traversing the troposphere, and how high-frequency fluctuation information contained in the wet delay component—Zenith Wet Delay (ZWD)—can be used to study atmospheric turbulence characteristics. In the presentation, Professor Deng showed results of spectral analysis and turbulence-parameter extraction from ZWD time series based on continuous observations from multi-system GNSS. Using the von Kármán turbulence spectrum model, and by fitting the ZWD power spectral density, two key parameters were retrieved: the fluctuation variance σ² and the cutoff frequency α. Combined with lidar and Sentinel satellite imagery for detailed, systematic analysis, the results indicate that both σ² and α derived from ZWD exhibit pronounced seasonal variations and closely follow changes in cloudiness and turbulent kinetic energy (TKE), peaking notably during convectively active summer periods. In addition, a four-hour sliding-window analysis revealed that short-term variations in α and σ² respond to rapid adjustments in wind speed and boundary-layer structure, thereby exposing multi-timescale turbulence features hidden in GNSS wet-delay signals. This study offers a new perspective for GNSS meteorology and opens a new avenue for monitoring atmospheric turbulence.After the presentation, participants engaged in in-depth discussions on topics such as applications of GNSS atmospheric remote-sensing technology and methods for extracting turbulence parameters, and they looked forward to future research. Suggestions included applying atomic clocks in the observation process to reduce the impact of clock bias, and mitigating multipath effects to further purify turbulence power spectra. Attending experts and scholars exchanged deeply on technology application bottlenecks, data-processing methods, and future research directions; the interplay of differing viewpoints broadened ideas for subsequent scientific collaboration and for solving technical challenges.The successful holding of this seminar not only promoted academic exchange on GNSS technology in the field of atmospheric remote sensing, but also provided a valuable learning platform for researchers in related fields. Participants unanimously agreed that Professor Deng’s report was detailed and insightful, playing an important leading role in GNSS atmospheric remote-sensing research and even opening up a novel research direction that will positively drive future work in related fields. 

The Inaugural Meeting of the IGS BAR Com...

On October 29, 2025 (Beijing Time), the IGS Bias and Ambiguity Resolution (BAR) Committee convened its inaugural meeting. The BAR Committee, which integrates the former "Bias & Calibration Working Group" and "the PPP-AR Pilot Project", has its core objective of coordinating the research, standardization, validation, and dissemination of satellite bias products for existing GNSS and future LEO satellites. Researcher Jianghui Geng from the PRIDE Research Group chaired the inaugural meetings. Dr. Wen Qiang from the PRIDE Research Group delivered a report titled Progress Report of the PPP-AR Pilot Project for 2024/2025, reviewing the work of the PPP-AR Pilot Project over the past year regarding orbit/clock/biases products. This year, BDS-3 PPP-AR product was included in the final combined product, thanks to the release of the HUS final BDS products. PPP-AR products from other Analysis Centers (ACs) of the IGS have also been updated. Specifically, EMR provides GPS code and phase OSBs in its OPS final products. WUM’s MGEX final products include QZSS phase OSBs, while GFZ MGEX rapid and GRG MGEX final products include code and phase OSBs for BDS satellites with PRN numbers higher than C46 (C47-C50).Additionally, during the meeting, Lotfi Massarweh from Delft University of Technology introduced the background, core objectives, work tasks, and charter of the newly established BAR Committee. Peter Steigenberger from the German Aerospace Center shared his research findings on the impact of GPS Flexible Power on the continuity of DCB estimation. Dr. Jiang Guo from the International Bureau of Weights and Measures presented his research on time transfer using continuous precise products.In the final discussion session of the meeting, participants focused on the future core work directions, technical challenges, and user needs of the IGS-BAR Committee. Key topics included GNSS flexible power, day-boundary bias handling methods, phase biases quality, and the development of the BAR official website.Over 60 experts, scholars, and researchers in the field of GNSS precise positioning from around the world attended the inaugural meeting. Through this meeting, all participants gained a clearer understanding of the BAR Committee’s work directions, PPP-AR technology progress, and the application of biases products. This will provide important guidance for the subsequent upgrade of GNSS high-precision services and the support for the development of LEO system.

International Workshop on Theories and F...

On October 26, Prof. Jianghui Geng was invited to attend the "International Workshop on Theories and Frontiers of GNSS Positioning: Advances in PNT, Remote Sensing, and Emerging Geospatial Technologies" at The Hong Kong Polytechnic University. During the workshop, Prof. Geng delivered a presentation on high-precision GNSS, covering fundamental GNSS theories, the International GNSS Service (IGS), the generation and integration of high-precision satellite products, the open-source software PRIDE PPP-AR, and the geohazard monitoring software platform GSeisRT. He also engaged in in-depth discussions with attendees from universities and research institutions.

PRIDE PPP-AR Version 3.2 with AI Integer...

On October 20, 2025, the PRIDE team at the State Key Laboratory of Precision Geodesy, Innovation Academy for Precision Measurement Science and Technology, CAS, released version 3.2 of PRIDE PPP-AR (https://github.com/PrideLab/PRIDE-PPPAR), which supports AI-based validation for undifferenced ambiguity resolution. This version integrates an XGBoost-based machine learning model for ambiguity validation through multi-dimensional indicators, including R-Ratio, Difference Test, Project Test, W-Ratio, ADOP, and the penalty factor λ. Combined with the LAMBDA method, it is designed for processing datasets with durations shorter than six hours and supports both single-system and multi-GNSS static and kinematic positioning. In tests conducted over the four years using stations independent of the training stations, this ML model consistently outperformed the classical Ratio Test, achieving a 5–10% improvement in validation accuracy (as shown below).Test result 1. Module Introduction Core Upgrade Module: arsig Module: The arsig module is the core upgrade in PRIDE PPP-AR v3.2, responsible for SDBS (single-difference between satellites) and ambiguity resolution, with a newly added AI-based integer ambiguity validation function. Basic Functionality: Utilizes SDBS to eliminate receiver-end hardware delays, handles wide-lane and narrow-lane ambiguities separately. Wide-lane ambiguities are uniformly resolved using integer rounding; narrow-lane ambiguities employ different resolution strategies based on data processing duration. Duration Adaptation Strategy: For processing duration > 6 hours, integer rounding is applied. For duration ≤ 6 hours, the default approach first reduces correlation using the LAMBDA method, followed by validation of fixed results via the XGBoost model. The core data processing flow of PRIDE PPP-AR 3.2 remains consistent with previous versions. the key enhancement is the integration of an AI validation step in the "ambiguity resolution phase" following the LAMBDA algorithm. The detailed workflow is illustrated below: Upon entering the ambiguity resolution stage: (1) Read base data and configurations: Load "amb_" files, "neq_" files, configuration files, etc., to obtain ambiguity-related settings while retrieving undifferenced ambiguity real-number solutions. (2) Wide-lane ambiguity processing: Calculate the SDBS wide-lane ambiguity estimate, then fix the SDBS wide-lane ambiguity using integer rounding. (3) Initial narrow-lane ambiguity calculation: Compute the SDBS narrow-lane ambiguity estimate. (4) Narrow-lane ambiguity resolution strategy selection: Rounding Method: Directly fix the SDBS narrow-lane ambiguity using integer rounding, then count the independent ambiguities that can be fixed for both wide-lane and narrow-lane ambiguities, and output them to the "cst_" file. LAMBDA+AI validation Method: Map the undifferenced covariance matrix to the SDBS correlation factor matrix, then use the LAMBDA method for fixing. Calculate parameters such as Ratio and ADOP values and input them into the XGBoost model for validation. If validation fails, reduce the number of candidate ambiguities and repeat the LAMBDA fixing process until validation succeeds. After successful validation, count the independent ambiguities and output them to the "cst_" file. Finally, incorporate strong constraints to output the fixed solution.2. Key Parameter Configuration (1) Ambiguity Resolution Method Parameter (-x <num> or --fix-method <num>) This parameter specifies the concrete method for ambiguity resolution, offering three options. By default, it automatically adapts based on processing duration: 1) Rounding Method: Directly fixes ambiguity by rounding, suitable for scenarios with longer processing times. 2) LAMBDA+Ratio validation Method: Reduces correlation using the LAMBDA method and validates the fixed result via the Ratio value (default validation threshold is 3). 3) LAMBDA + AI Validation Method: Reduces correlation using the Lambda method and validates the fixed result through an XGBoost model. Default Rules: For processing duration under 6 hours, automatically applies Method 3) Lambda+AI Validation; Ratio Test optional (user-specified). For processing duration ≥ 6 hours, automatically applies Method 1) Rounding Method. (2)AI Ambiguity Validation Switch in Configuration File This configuration controls whether AI validation is enabled, interacting with the "--fix-method" parameter: Value "YES": Enables XGBoost model validation for ambiguity resolution, corresponding to "--fix-method 3". Value "NO": Disables AI validation. Uses the Ratio value to determine fixed results, corresponding to "--fix-method 2". The specific Ratio validation threshold is determined by the "Critical search" configuration option.ReferencesGuo, J., Geng, J. Integer ambiguity validation through machine learning for precise point positioning. Satell Navig 6, 14 (2025). https://doi.org/10.1186/s43020-025-00167-8

PRIDE Team Participates in the IAG2025 C...

From August 31 to September 6, 2025, the PRIDE team participated in the IAG-2025 Conference held in Rimini, Italy. The theme of this conference is "Geodesy for a Changing Environment", which provides an important opportunity for the international academic community to conduct in-depth exchanges and discussions on the key role of geodetic science in relevant fields. The conference theme aims to promote the geodetic community to focus on the impacts brought by environmental changes, pay attention to the increasingly severe various extreme events, and promote the formation of scientific and reasonable strategies to effectively identify and respond to potential sudden changes in the Earth system.Prof. Jianghui Geng delivered a presentation titled "High-Precision Broad-Bandwidth Deformation Monitoring Using Mass-Market GNSS/Accelerometers". This research adopts an inter-satellite single-difference fusion scheme, which breaks free from the reliance on reference stations and effectively overcomes the issue of unstable clocks in smartphones. Consequently, it achieves centimeter-level broadband deformation monitoring based on mass-market smartphones. The research results indicate that mass-market GNSS/accelerometer devices hold significant potential in constructing low-cost and high-density observation networks.Prof. Jianghui Geng delivered a report titled "GNSS Ambiguity Validation through Machine Learning". The report mainly introduced the use of machine learning to replace the traditional ratio value for the correctness test of ambiguity fixing. The accuracy has been greatly improved compared with the traditional ratio test in each arc segment and each satellite system. The report also introduced how to use machine learning to process data in the upcoming new version of the PRIDE-PPP -AR open-source software.Master Long Zhao delivered a presentation titled "Subcarrier Observations from Wideband Signals for High-precision GNSS Positioning", introducing the team's latest research progress in high-precision positioning using subcarrier observations. The research results show that compared with traditional pseudoranges, subcarrier observations have lower noise levels and stronger anti-multipath capabilities, demonstrating broad application prospects in high-precision positioning.