###### Abstract  
Low Earth Orbit (LEO) satellites utilizing Doppler measurements can be an effective supplementary positioning solution when Global Navigation Satellite System (GNSS) signals are unavailable. LEO satellites pose challenges to the efficiency and stability of real-time satellite selection algorithms due to their high dynamic and large number. The traditional satellite selection algorithms have the problems of high computational complexity and significant hardware dependence. In contrast, the intelligent optimization algorithm significantly improves the accuracy and real-time performance of satellite selection through global search and efficient processing. According to the characteristics of LEO satellites, a Multi-Strategy Fusion Grey Wolf Optimization (MSFGWO) algorithm is proposed for satellite selection. The experimental results show that when six satellites are selected, the average Doppler Geometric Dilution of Precision (DGDOP) value of the MSFGWO algorithm is 222.08. Compared with the DGDOP ratio of the traversal method, it is 1.03. The three-dimensional positioning accuracy is 192.86 m, and the positioning error is improved by 54.43% compared with the positioning accuracy of the traditional GWO algorithm. The longest continuous observation was achieved for 45 s, during which no switching of six satellites occurred at adjacent moments. The calculation time of the algorithm was only 0.0174 s, and the efficiency was improved by 93.43%. The MSFGWO algorithm proposed in this paper not only improves the overall optimization ability of the Grey Wolf Optimizer (GWO) algorithm and effectively reduces the DGDOP value but also significantly reduces the satellite switching number and prolongates the continuous observation time, thus improving the stability and accuracy of the positioning solution. LEO constellation; satellite selection; grey wolf optimization algorithm; computational efficiency 2025, 17, 1320 [[https://doi.org/10.3390/rs17081320130309/rs1708132013009/rs1708132](https://doi.org/10.3390/rs17081320130309/rs1708132013009/rs1708132)]([https://doi.org/10.3390/rs17081320130309/rs1708132013009/rs1708132](https://doi.org/10.3390/rs17081320130309/rs1708132013009/rs1708132))and latency due to their relatively low orbital altitude, have emerged as an effective supplementary positioning solution when GNSS are unavailable [2; 3; 4; 5]. Currently, the global construction of LEO satellite constellations has entered a phase of rapid deployment. The Starlink constellation, developed by the US company SpaceX, has successfully achieved effective mitigation of self-interference among satellites through the implementation of advanced routing algorithms and optimized frequency allocation techniques [6; 7]. The OneWeb constellation comprises a hybrid system of 720 satellites in orbit, designed to establish a low-latency and high-speed global communication network [8; 9]. The Amazon Kuiper system is designed to deliver global network services utilizing a constellation of over 3000 satellites [10]. Projects such as China's Apocalypse Constellation [11] and Qianfan Constellation [12] are currently being actively pursued and developed. These large-scale constellation deployments enable single-point observations to simultaneously capture dozens of satellites, thereby significantly enhancing the system's service capabilities [13]. However, the dynamic characteristics of LEO satellites present significant challenges for the navigation and positioning system. The maximum duration of visibility for a single LEO satellite is limited to 10 to 15 min, and its rapid motion results in substantial Doppler frequency shifts. The low orbit reduces the duration of visibility over the ground, necessitating frequent switching between satellites or beams by ground user terminals. This not only compromises the continuity of communication but also has the potential to cause signal interruptions or degradation in quality.