Trajectory optimization of high-altitude balloon in nearspace-ground collaborative observation
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摘要:
高空气球与地基平台组网开展协同观测的需求日益迫切,覆盖一致性是其关键问题之一,面临网络拓扑时变、气球调控能力受限、临近空间风场复杂等多重挑战。为改善高空气球与地基站网协同观测的覆盖一致性,以带有副气囊且不配备动力装置的高空气球为研究对象,从垂直方向和水平方向两方面分析高空气球轨迹调控方法,研究高空气球对地观测覆盖区域,针对高空气球位置时变的特征,设计了临地协同观测覆盖一致性评价指标,提出基于鲸鱼算法的高空气球组网轨迹优化方法,并针对多种输入条件对该方法进行了仿真验证。仿真结果表明:所提方法能够大幅改善临地协同观测的覆盖一致性,尤以夏秋季准零风层存在的情况下改善效果更为明显。
Abstract:The requirement of collaborative observation by high-altitude balloon network and ground-based network is increasingly urgent. And coverage consistency is one of its critical problems affecting observation performance, which faces many challenges such as time-varying network topology, limited balloon control ability, and complicated wind field in near space. To improve the coverage consistency of high-altitude balloon network and ground-based network in cooperative observation, high-altitude balloon with secondary airbag but without propulsion device is studied, its trajectory control approach is analyzed from both the vertical direction and the horizontal direction, and its coverage in earth observation is discussed. Considering the time-variant position of high-altitude balloons, a performance index is designed to evaluate the coverage consistency, and a trajectory optimization algorithm for high-altitude balloon is proposed based on whale optimization algorithm. Simulations are carried out under many inputs. And simulation results show that the proposed algorithm can improve the coverage consistency significantly, especially in summer and autumn wind fields with quasi-zero wind layer.
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表 1 地基站网仿真参数
Table 1. Simulation parameters of ground-based platforms
地基测站 经度/(°) 纬度/(°) 观测覆盖半径/km 地基测站1 96.0 38.5 200 地基测站2 97.5 40.0 200 地基测站3 99.0 38.0 200 表 2 高空气球仿真参数
Table 2. Simulation parameters of high-altitude balloons
气球 初始经度/(°) 初始纬度/(°) 初始飞行
高度/km最低飞行
高度/km最高飞行
高度/km副气囊内初始
空气质量/kg阀门开口
半径/m单位时间
进气量/ (m3·s−1)高空气球1 96 41 21 20 24 144.7 0.15 0.3 高空气球2 97 41 22 20 24 111.1 0.15 0.3 表 3 轨迹优化结果与无轨迹优化结果对比
Table 3. Performance comparison between optimized results and unoptimized results
结果类型 临地协同观测覆盖一致性/% 轨迹优化结果 24.45 无轨迹优化结果 14.61 表 4 高空气球初始网络布局
Table 4. Initial network layout of high-altitude balloons
布局 气球1
初始
经度/(°)气球1
初始
纬度/(°)气球1
初始
高度/km气球2
初始
经度/(°)气球2
初始
纬度/(°)气球2
初始
高度/km布局1 97 41 22 97 41 22 布局2 97 41 20 97 41 24 布局3 97 41 22 100 38 22 布局4 97 41 20 100 38 24 表 5 高空气球初始网络布局对协同观测性能的影响对比
Table 5. Comparison of influence of initial network layout of high-altitude balloons on collaborative observation performance
布局 轨迹优化后的临地协同
观测覆盖一致性/%无轨迹优化的临地协同
观测覆盖一致性/%布局1 23.95 4.00 布局2 23.97 4.97 布局3 26.64 13.09 布局4 26.83 12.26 表 6 不同风场的轨迹优化结果对比
Table 6. Comparison of trajectory optimization results for different wind fields
风场 轨迹优化后的临地协同
观测覆盖一致性/%无轨迹优化的临地协同
观测覆盖一致性/%3月 1.08 0.88 6月 24.45 14.61 9月 8.56 7.48 12月 0.87 0.77 表 7 不同高度调控能力的轨迹优化结果对比
Table 7. Comparison of trajectory optimization results with different height control capabilities
风场 气球高度调控范围为20~
24 km的临地协同
观测覆盖一致性/%气球高度调控范围为18~
26 km的临地协同
观测覆盖一致性/%3月 1.08 1.17 6月 24.45 24.77 9月 8.56 10.04 12月 0.87 0.91 -
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