基于多项式代理的空间碎片群高效轨道预报

  • 董一超 ,
  • 代洪华 ,
  • 王昌涛 ,
  • 杨文传 ,
  • 石琳
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  • 西北工业大学

收稿日期: 2026-02-09

  修回日期: 2026-07-03

  网络出版日期: 2026-07-16

基金资助

国家杰出青年科学基金;国家自然科学基金;科技部重点研发计划项目

Efficient orbit prediction for space debris cluster based on polynomial surrogate

  • DONG Yi-Chao ,
  • DAI Hong-Hua ,
  • WANG Chang-Tao ,
  • YANG Wen-Chuan ,
  • SHI Lin
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Received date: 2026-02-09

  Revised date: 2026-07-03

  Online published: 2026-07-16

Supported by

National Science Fund for Distinguished Young Scholars;National Natural Science Foundation of China;National Key Research and Development Program of China

摘要

针对大规模空间碎片群进行快速精确的轨道确定与预报,是提升空间碰撞预警能力的重要基础。然而,现有高精度数值方法严重依赖小步长的逐目标数值积分,计算复杂度随目标数量快速增长,难以满足大规模碎片群轨道递推的效率需求。为克服上述困难,提出了一种基于多项式代理的空间碎片群高效半解析轨道预报方法。首先,基于Jet Transport技术和Chebyshev多项式近似,构建了碎片群轨道初值至任意时刻轨道状态的高阶多项式代理模型;其次,引入大步长并行计算的反馈加速Picard迭代法,进一步提升了计算效率;而后,基于相空间分割制定了标称轨道选取策略,有效抑制了多项式代理模型在碎片群边界处的误差发散;最后,基于NASA标准解体模型生成卫星爆炸解体碎片初始数据,在LEO、HEO与GEO场景下对不同碎片群开展了短期轨道预报仿真。仿真结果表明,当平均预报误差设定在1m范围内时,所提JT-Chebyshev方法较蒙特卡洛方法计算效率提高了150倍以上。

本文引用格式

董一超 , 代洪华 , 王昌涛 , 杨文传 , 石琳 . 基于多项式代理的空间碎片群高效轨道预报[J]. 航空学报, 0 : 1 -0 . DOI: 10.7527/S1000-6893.2026.33492

Abstract

Rapid and precise orbit determination and prediction for large-scale debris cluster serve as crucial foundations for enhancing collision warning capabilities. However, existing high-precision numerical methods rely on small-step, object-wise integration, leading to poor scalability with respect to the number of debris objects and limiting efficiency for large-scale debris propagation. To address this issue, this paper proposes an efficient semi-analytical orbit prediction method for space debris cluster based on polynomial surrogate. Firstly, this method constructs a high-order polynomial surrogate model mapping initial orbital states of debris to orbital states at any given time using Jet Transport and Chebyshev approximation. Then, the feedback-accelerated Picard iteration method with large-step parallel computation is introduced to further improve efficiency. Moreover, a nominal orbit selection strategy based on phase-space partitioning is developed to suppress error divergence in the polynomial surrogate model near debris cluster boundaries. Finally, using initial debris values generated from the NASA standard breakup model, short-term orbit prediction simulations for different space debris clusters in LEO, HEO, and GEO scenarios are conducted. Results show that, when average prediction error is set within 1 meter, the proposed JT-Chebyshev method improves computational efficiency by over 150 times compared to the Monte Carlo method.

参考文献

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