Optimization Strategy for Single-satellite to Multi-station Data Transmission
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摘要: 针对低轨遥感卫星多站数传接力问题中链路切换时刻选择及接力场景复杂的问题, 提出了一种基于链路切换时间优化的多站数传接力方法, 简化多站接力场景并选择最优接力时刻, 提升数传接力传输时长. 在该方法中, 首先建立多站接力的数学描述, 并构建卫星与地面站链路切换时间的表达方法. 基于主流的低轨遥感卫星和地面站特征, 建立星地数传接力场景, 归纳可见时间弧段特征, 构建多站接力复杂场景的两站化优化策略, 同时对链路切换时间进行数值求解, 寻求接力时间最短的接力时刻. 最后, 使用典型的星地数传模型仿真计算验证本文构建的带有优化策略的数传接力方法. 仿真结果表明: 在国内三个典型地面站场景下, 卫星和地面站的数传链路存在32.0%可接力数传弧段, 其中三站接力场景占比17.9%, 三站接力场景可以通过优化策略简化成两站接力场景并存在最优接力时刻, 使用接力时间优化策略后, 最短链路切换时间相比最长接力时间可缩短最高达25%; 使用优化后的数传接力方法进行接力数传, 每次可用时间的平均值由单站的7.61 min提升为11.12 min.Abstract: In order to solve the problems of link handover time selection and complex relay scenarios in the multi-station data relay problem, a multi-station data relay method based on link handover time optimization was proposed, which simplified the multi-station relay scene and selected the optimal relay time, so as to improve the transmission time of data relay transmission. In this method, the mathematical description of multi-station relay is established based on the satellite-ground model and the motion constraints of the mechanical antenna, and the expression method of the link switching time between the satellite and the ground station is constructed. Based on the characteristics of mainstream low-orbit remote sensing satellites and ground stations, the relay scenarios of satellite-to-ground data transmission are established, the characteristics of their visible time arcs are summarized, and a two-station optimization strategy for complex multi-station relay scenarios is constructed. Finally, the typical satellite-to-ground data transmission model simulation is used to verify the data transmission relay method with optimization strategy constructed in this paper. The simulation results show that there are 32.0% relayable data transmission arcs in the data transmission links between satellite and the three typical ground station located in China, of which the three-station relay scenario accounts for 17.9%, and the three-station relay scenario can be simplified into a two-station relay scenario through the optimization strategy. In the link handover interval of multiple stations with visible arcs, there is a relay time with the shortest relay time, and the shortest link switching time can be shortened by up to 25% compared with the worst relay time after using the relay time optimization strategy. Using the optimized data relay method for relay data transmission, the average time available for each time was increased from 7.61 minutes to 11.12 minutes.
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表 1 地面站参数
Table 1. Parameter of ground station
序号 站名称 经度/(º)E 纬度/(º) 高程/m 最低接收仰角/(º) 1 密云站 116.8 E 40.4 N 109 5 2 喀什站 75.9 E 39.51 N 1307 5 3 三亚站 109.3 E 18.31 N 22 7 表 2 三站接力信息
Table 2. Simulation result of three station relay
入站时刻
积秒/s出站时刻
积秒/ s可见时长/
min地面站 前序站出站与后序
站入站间隔时间/ min190690.5 191150.5 7.666 三亚 80.034 191123.1 191411.8 4.811 密云 –0.45597 191217.4 191506.9 4.824 喀什 –3.23952 表 3 多站接力策略下的数传时间对比
Table 3. Comparison of data transmission time of the multi-station relay strategy
名称 平均值 最大值 最小值 接力后每天通信时间/min 66.78 72.56 56.37 独立站每次可通信时间/min 7.61 9.13 5.92 接力站每次可通信时间/min 11.12 11.81 9.61 独立站每天可见次数 4.375 5 2 接力站每天可见次数 6.19 8 6 -
[1] HARRIS A, VALADE T, TEIL T, et al. Generation of spacecraft operations procedures using deep reinforcement learning[J]. Journal of Spacecraft and Rockets, 2022, 59(2): 611-626 doi: 10.2514/1.A35169 [2] 何奇恩, 李峰, 钟兴. 多目标算法在卫星区域覆盖调度及数传规划上的应用综述[J]. 遥感技术与应用, 2023, 38(4): 783-793HE Qi'en, LI Feng, ZHONG Xing. A review of the application of multi-objective algorithms in satellite regional coverage scheduling and data transmission planning[J]. Remote Sensing Technology and Application, 2023, 38(4): 783-793 [3] 刘振星. 面向遥感卫星的综合电子系统研究[D]. 合肥: 中国科学技术大学, 2021LIU Zhenxing. Research on Integrated Avionics for Remote Sensing Satellite[D]. Hefei: University of Science and Technology of China, 2021 [4] ZHANG J R, ZHU S B, BAI H F, et al. Optimization strategy to solve transmission interruption caused by satellite-ground link switching[J]. IEEE Access, 2020, 8: 32975-32988 doi: 10.1109/ACCESS.2020.2973698 [5] 陈宇, 张勇, 陈实. 大规模卫星集群网络自适应加权分簇算法[J]. 北京理工大学学报, 2021, 41(11): 1188-1192CHEN Yu, ZHANG Yong, CHEN Shi. Adaptive weighted clustering algorithm for large-scale satellite cluster network[J]. Transactions of Beijing Institute of Technology, 2021, 41(11): 1188-1192 [6] SPANGELO S, CUTLER J, GILSON K, et al. Optimization-based scheduling for the single-satellite, multi-ground station communication problem[J]. Computers :Times New Roman;">& Operations Research, 2015, 57: 1-16 [7] 曾麒麟, 于锡峥, 熊蔚明. 太阳观测卫星的数传天线波束及其指向设计[J]. 国防科技大学学报, 2019, 41(6): 135-142 doi: 10.11887/j.cn.201906020ZENG Qilin, YU Xizheng, XIONG Weiming. Design of data transmission antenna beam angles and directions for solar observatory satellite[J]. Journal of National University of Defense Technology, 2019, 41(6): 135-142 doi: 10.11887/j.cn.201906020 [8] 常飞. 卫星地面站数传资源配置优化模型与算法研究[D]. 长沙: 国防科技大学, 2010CHANG Fei. Research on Optimization Model and Algorithm for Ground Station Data Transmission Resources Allocation[D]. Changsha: National University of Defense Technology, 2010 [9] 王长红, 高飞, 杜伟. 基于星载高速调制器的预失真算法研究[J]. 北京理工大学学报, 2020, 40(9): 988-993WANG Changhong, GAO Fei, DU Wei. Study on predistortion algorithm of spaceborne high rate modulator[J]. Transactions of Beijing Institute of Technology, 2020, 40(9): 988-993 [10] 张鑫宇, 杨甲森, 徐聪, 等. CPU-GPU协同高性能卫星数传预处理方法[J]. 上海航天(中英文), 2023, 40(4): 38-45ZHANG Xinyu, YANG Jiasen, XU Cong, et al. High-performance pre-processing method for transmission data based on CPU-GPU collaboration[J]. Aerospace Shanghai (Chinese :Times New Roman;">& English), 2023, 40(4): 38-45 -
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