随着巨型星座的卫星数量激增，星座轨道仿真与可视化所需的计算资源急剧增加。为解决巨型星座在存储空间与算力受限的移动设备上可视化效率低下的问题，提出一种基于HDBSCAN算法的轨道模型简化方法。该方法采用两步聚类策略，首先对星座轨道进行类别划分，然后在各类别内进一步细分轨道面，并以聚类中心作为简化表示。以Starlink星座为例，结果显示，轨道数据从6 778条压缩至279条。在本实验硬件环境下，可视化帧率得到大幅提升，且简化后的轨道模型有效保留了巨型星座的结构特征。

With the surge in the number of satellites in mega-constellations， the computational resources required for constellation orbit simulation and visualization have increased dramatically. To address the issue of inefficient visualization of mega-constellations on mobile devices with limited storage and computational power， this paper proposes an orbit model simplification method based on the HDBSCAN algorithm. This method employs a two-step clustering strategy： first， categorizing the constellation orbits， and then further subdividing the orbital planes within each category， using the cluster centers as simplified representations. Using the Starlink constellation as an example， experiments show that the orbit data is compressed from 6 778 to 279 tracks. Under the experimental hardware environment， the visualization frame rate is significantly improved， and the simplified orbit model effectively retains the structural characteristics of the mega-constellation.