研究目的
Investigating the resource scheduling optimization for data relay satellite system with microwave and laser hybrid links to address the oversubscription problem of data relay access request of user stars in future Space-Based Information System.
研究成果
The hybrid optimization algorithm combining artificial immune strategy, niche idea, and improved genetic algorithm effectively solves the static resource scheduling problem for data relay satellite systems with microwave and laser hybrid links. It demonstrates superior performance in convergence speed and scheduling efficiency compared to standard genetic algorithms, making it suitable for multi-task, multi-antenna systems.
研究不足
The study focuses on static resource scheduling and may not fully address dynamic changes in task priorities or resource availability. The simulation scenario is limited to a specific set of user satellites and relay satellite configurations.
1:Experimental Design and Method Selection:
The study establishes a multi-objective programming model on static resource scheduling constraint satisfaction problem and proposes a hybrid optimization algorithm combining artificial immune strategies, niche ideas, and improved genetic algorithm.
2:Sample Selection and Data Sources:
The simulation scenario includes a relay satellite located at 10° east longitude with three single-address antennas (S-band, Ku-band, and optical antenna). User satellites' parameters are imported in STK for visibility analysis.
3:List of Experimental Equipment and Materials:
The study uses STK for analysis and simulation, with specific parameters for antennas and user satellites provided.
4:Experimental Procedures and Operational Workflow:
The hybrid optimization algorithm is applied to solve the scheduling model, with the algorithm's performance compared against a standard genetic algorithm.
5:Data Analysis Methods:
The study compares the completion of priority-weighted tasks of the two algorithms and analyzes the search process, individual repetition rates, and scheduling efficiency.
独家科研数据包,助您复现前沿成果,加速创新突破
获取完整内容