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高轨预警星座由若干颗地球静止轨道卫星和大椭圆轨道卫星组成,星座优化的目标是满足重点监视区域的覆盖和提高覆盖区域的定位精度。对于覆盖性优化,根据多个监视区域的威胁等级,星座系统需要提供不同的覆盖重数;对于定位精度优化,系统在立体观测和单星观测情况下存在很大差异。因此高轨预警星座优化是一个复杂多区域多目标优化问题。针对以上难点,提出了多层次多目标优化模型,可以较完整合理地描述预警星座优化问题;在优化模型求解方面,将优化计算分为覆盖性优化和定位精度优化两个环节;在覆盖性优化环节,提出了基于搜索空间变换的覆盖性快速优化方法,提高了Pareto最优解的计算速度和准确性。在定位精度优化环节,采用序优化方法进一步缩短优化时间。仿真试验表明,该方法可设计出满足预警任务需求的星座,且优化耗时在1min以内,能有效地缩短预警星座优化时间。
The high-altitude warning constellation consists of a number of geostationary satellites and large elliptical orbit satellites. The goal of constellation optimization is to meet the coverage of the key surveillance area and improve the positioning accuracy of the coverage area. For coverage optimization, the constellation system needs to provide different coverage weights according to the threat level of multiple surveillance areas. For the optimization of positioning accuracy, the system varies greatly between stereo observation and single-satellite observation. Therefore, the constellation optimization of high-rail warning is a complex multi-region multi-objective optimization problem. In view of the above difficulties, a multi-level multi-objective optimization model is proposed, which can describe the warning constellation optimization problem in a more complete and reasonable manner. In the optimization model, the optimization calculation is divided into coverage optimization and positioning accuracy optimization. , A rapid coverage optimization method based on search space transformation is proposed and the calculation speed and accuracy of Pareto optimal solution are improved. In the optimization of positioning accuracy, the optimization method is used to further optimize the optimization time. Simulation results show that this method can design constellations that meet the needs of early warning tasks and optimize the time consumption within 1min, which can effectively shorten the time of early warning constellation optimization.