A new study reveals advanced methods for improving orbit determination (OD) of large constellations of Low Earth Orbit (LEO) satellites, utilizing Global Navigation Satellite System (GNSS) observations and inter-satellite ranging. These innovations promise to significantly boost the accuracy and computational efficiency essential for satellite communication, remote sensing, and navigation augmentation.
Large constellations of Low Earth Orbit (LEO) satellites are integral to modern satellite communication, remote sensing, and navigation systems. However, tracking the orbits of these satellites poses a significant challenge due to their vast numbers and the need for high-precision data over long periods. Ground-based tracking stations are limited in their ability to handle such vast constellations, while spaceborne Global Navigation Satellite System (GNSS) receivers offer a promising solution. Unfortunately, existing methods still struggle with computational efficiency and accuracy, necessitating the development of more advanced techniques.
Published (DOI: 10.1186/s43020-025-00160-1) on February 10, 2025, in Satellite Navigation , a new study from the Xi'an Research Institute of Surveying and Mapping and the State Key Laboratory of Spatial Datum presents stepwise autonomous orbit determination (OD) methods for large LEO constellations. By combining GNSS observations with inter-satellite ranging, the research significantly enhances both the accuracy and efficiency of OD—an essential component of satellite functionality.
The study introduces three pioneering autonomous OD strategies. The first method integrates GNSS data with inter-satellite link (ISL) range measurements to refine orbit parameters. The second method utilizes ISL ranges as constraints, improving accuracy without adding computational load. The third strategy adapts the covariance matrix of orbit predictions dynamically, addressing errors caused by abnormal dynamic model information. These approaches begin with initial orbit parameter estimation via spaceborne GNSS observations, followed by refinements using ISL range data. The adaptive approach stands out by adjusting the covariance matrix based on an adaptive factor, which controls dynamic model errors. Simulations demonstrate substantial improvements, with the root mean square error (RMSE) of position estimates dropping to as low as 11.34 cm when combining dynamic models with ISL ranges. Moreover, the ability to parallelize the estimation process for individual satellites reduces computational burden, offering a scalable solution for managing large constellations.
Dr. Yuanxi Yang, a leading expert in satellite navigation and one of the study's authors, underscores the importance of these advancements: "Our stepwise autonomous OD methods provide a practical solution to the computational and accuracy challenges faced by large LEO constellations. By integrating GNSS observations and ISL ranging, we achieve higher precision and efficiency, paving the way for more robust satellite operations."
The implications of this research are far-reaching. The enhanced OD techniques provide a scalable solution that will improve the operational efficiency of large LEO constellations, ensuring more accurate satellite communication, remote sensing, and navigation augmentation. As satellite constellations grow in size and complexity, these methods offer a reliable framework for maintaining precise orbit control—unlocking vast potential for global navigation, environmental monitoring, and beyond.
