随着星间链路技术的发展，激光星间链路以其独特的优势得到了广泛的关注。相比现有的全球导航卫星系统(GNSS) 采用的微波星间链路，无论在测距精度还是通信带宽上，以激光为媒介的星间通信更具优势。因此，在下一代GNSS 建设中，系统组网方式将从全微波星间链路转变为以激光星间链路为主。然而，在系统过度阶段，即“局部激光 +微波”，局部高速激光节点的部署是亟需解决的关键技术问题。为了解决上述问题，本文提出了一种提出了一种基于带精英策略的非支配排序遗传算法的多目标离散二进制选择算法（M-DBSA）来选择高速激光节点。首先，基于星间几何约束和天线俯仰角约束分析，建立了一个高中低星间可视性模型。其次，为了提升混合体制 GNSS 星间链路通信能力，采用M-DBSA 得到优化的联合策略。最后，相比于所对比的算法，实验结果表明所提出的算法能进一步提升激光骨干节点对低轨卫星的覆盖性，缩短高速激光骨干节点对低轨卫星的重访时间约 49%，并且保持了较好通信跳数分布。

With the development of inter-satellite link technology, laser inter-satellite link have garnered widespread attention due to its unique advantages. Compared to the current Global Navigation Satellite System (GNSS) that uses microwave inter-satellite links, laser-based inter-satellite communication offers advantages in terms of both ranging accuracy and communication bandwidth. Consequently, the network configuration of the next-generation GNSS will transition from relying entirely on microwave inter-satellite links to primarily using laser inter-satellite links. However, during the transition phase, where both laser and microwave links coexist, the deployment of high-speed laser nodes is critical technical challenge that need to be addressed. To solve these challenges, this paper proposes a Multi-objective Discrete Binary Selection Algorithm (M-DBSA) based on a Non-dominated Sorting Genetic Algorithm with an elite strategy. Firstly, a high-medium-low inter-satellite visibility model is established based on inter-satellite geometric constraints and antenna elevation angle constraints. Secondly, Secondly, to enhance the communication capability of inter-satellite links in hybrid GNSS systems, an optimized joint strategy is obtained using the M-DBSA algorithm. Finally, the experiment results demonstrate that the proposed algorithm can further improve the coverage of laser backbone nodes to low-orbit satellites, shorten the revisit time of high-speed laser backbone nodes to low-orbit satellites by about 49%, and maintain a better distribution of communication hops compared to the comparison algorithms.