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In recent years, the large Low Earth Orbit (LEO) constellations have become a hot topic due to their great potential to improve the Global Navigation Satellite Systems (GNSS) positioning performance. One of the important focus is how to obtain the accurate and reliable orbits for these constellations with dozens of LEO satellites. The GNSS-based Precise Orbit Determination (POD) will be exclusively performed to achieve this goal, where the Integer Ambiguity Resolution (IAR) plays a key role in acquiring high-quality orbits. In this study, we present a comprehensive analysis of the benefit of the single-receiver IAR in LEO POD and discuss its implication for the future LEO constellations. We perform ambiguity-fixed LEO POD for four typical missions, including Gravity Recovery and Climate Experiment (GRACE) Follow-On (GRACE-FO), Swarm, Jason-3 and Sentinel-3, using the Uncalibrated Phase Delay (UPD) products generated by our GREAT (GNSS+ REsearch, Application and Teaching) software. The results show that the ambiguity fixing processing can significantly improve the accuracy of LEO orbits. There are negligible differences between our UPD-based ambiguity-fixed orbits and those based on the Observable Signal Bias (OSB) and Integer Recovery Clock (IRC) products, indicating the good-quality of UPD products we generated. Compared to the float solution, the fixed solution presents a better consistency with the external precise science orbits and the largest accuracy improvement of 5 mm is achieved for GRACE-FO satellites. Meanwhile, the benefit can be observed in laser ranging residuals as well, with a Standard Deviation (STD) reduction of 3–4 mm on average for the fixed solutions. Apart from the absolute orbits, the relative accuracy of the space baseline is also improved by 20–30% in the fixed solutions. The result demonstrates the superior performance of the ambiguity-fixed LEO POD, which appears as a particularly promising technique for POD of future LEO constellations. [ABSTRACT FROM AUTHOR]

Precise knowledge of orbit represents a fundamental requirement for the earth observing satellite missions to achieve their advanced objectives. The integer ambiguity resolution (IAR) has proved to be a key to utmost accuracy in space navigation. Generally, there are two typical IAR methods widely used in the orbit determination of low Earth orbit (LEO) satellites, the classical double‐difference (DD) IAR and new single‐difference (SD) IAR. Based on one‐year observations of Gravity Recovery and Climate Experiment Follow‐On (GRACE‐FO) and Sentinel‐3 missions, this study is dedicated to a comprehensive analysis of the differences of the products used, implementation details and ambiguity fixing performance for different IAR methods in LEO precise orbit determination (POD), and discusses how these differences influence the orbit solutions. The results show that the orbit accuracy improvement contributed by the ambiguity fixing varies with the adopted IAR methods. SD IAR can contribute to a representative reduction of 1–4 mm in satellite laser ranging (SLR) residuals compared to the float solutions. The application of bias products from different analysis centers leads to marginal differences for the ambiguity fixing. For DD IAR method, the different ways to form the double‐difference ambiguity yield different performances in POD. The DD IAR of space‐ground baselines can achieve a comparable performance to SD IAR, while the benefit of ambiguity fixing is largely weakened when forming space‐space baseline. Furthermore, we also analyze the contribution of the ambiguity fixing to the accuracy and robustness of the kinematic orbit and discuss its great potential for the future applications. Plain Language Summary: Obtaining accurate orbit information of low Earth orbit satellite is an essential prerequisite for the geodetic and remote sensing missions to support their operation. Today, the onboard Global Navigation Satellite System (GNSS) technology has been commonly recognized as the optimal way to produce high‐quality orbit for these Earth‐observation satellites. However, due to the existence of hardware delays in both signal transmitter and receiver, the inherent accuracy of carrier phase signal is not fully exploited. Removing the effects of these errors plays a key to achieve the ultimate accuracy of GNSS‐based orbit. Nevertheless, different methods of separating these hardware delays from GNSS observations eventually lead to accuracy discrepancy in satellite orbit recovery. Our study focuses on the several commonly used methods of eliminating the hardware delays in the precise orbit determination. We present a detailed analysis about the differences between these methods lying in the implementation details and performance, and discuss how these differences impact the orbit solutions. Using a wider set of Earth‐observation missions and data over a longer time span than before, we aim to answer the question which method is optimal or most appropriate for the recovery of satellite orbit and make suggestion for the future mission. Key Points: The differences in the implementation, fixing performance and accuracy between several ambiguity fixing methods in low Earth orbit (LEO) precise orbit determination (POD) are discussedThe single‐receiver integer ambiguity resolution represents the currently optimal choice for LEO PODWith the integer ambiguity fixing method, the kinematic orbit exhibits a great potential for the future applications [ABSTRACT FROM AUTHOR]

• An efficient parallel approach for multi-GNSS real-time precise orbit determination is proposed. • The proposed method improves computational efficiency by 70% compared with the traditional method. • Quad-system real-time POD with 90 stations can be completed within 5 s. Real-time Global Navigation Satellite System (GNSS) precise orbits are essential prerequisites for real-time GNSS-based applications. However, the high computational demands of filter-based real-time multi-GNSS POD methods present a significant challenge for practical utilization. This study introduces an efficient parallel approach for quad-constellation GNSS real-time POD using the square root information filter (SRIF). In the proposed approach, parallel QR factorization algorithms are implemented to expedite parameter estimation based on SRIF, while parallel processing model is designed for real-time POD to enhance its computational efficiency. Validation experiments show that the computation time for measurement and time update in SRIF can be reduced by 78.5% and 80.5%, respectively, compared to the traditional serial approach. Additionally, parallel computing improves the computational efficiency of GNSS processing algorithms in real-time POD by approximately 70%. The proposed approach enables the completion of quad-system real-time POD solutions with 90 stations within 5 s, representing an impressive 73.0% reduction. [ABSTRACT FROM AUTHOR]