系统工程与电子技术 ›› 2024, Vol. 46 ›› Issue (8): 2789-2797.doi: 10.12305/j.issn.1001-506X.2024.08.26

• 制导、导航与控制 • 上一篇    下一篇

天基分布式无源探测的空间多目标跟踪方法

江林海1, 龚柏春1,*, 刘传凯2,3, YANG Yang4, 张仁勇5   

  1. 1. 南京航空航天大学航天学院, 江苏 南京 210016
    2. 北京航天飞行控制中心, 北京 100190
    3. 航天飞行动力学技术重点实验室, 北京 100190
    4. 新南威尔士大学机械与制造工程学院, 悉尼 2052
    5. 中国科学院空间应用工程与技术中心, 北京 100094
  • 收稿日期:2023-05-30 出版日期:2024-07-25 发布日期:2024-08-07
  • 通讯作者: 龚柏春
  • 作者简介:江林海(1998—), 男, 硕士研究生, 主要研究方向为空间多目标跟踪定轨
    龚柏春(1987—), 男, 副研究员, 硕士研究生导师, 博士, 主要研究方向为空间非合作目标态势感知、飞行器集群导航与控制
    刘传凯(1983—), 男, 高级工程师, 博士, 主要研究方向为视觉导航、空间机械臂操作规划
    YANG Yang (1988—), 男, 讲师, 博士, 主要研究方向为空间飞行导航、态势感知
    张仁勇(1984—), 男, 副研究员, 博士, 主要研究方向为轨道动力学与控制
  • 基金资助:
    国家自然科学基金面上项目(12272168);国家自然科学基金面上项目(42271448);空间智能控制技术全国重点实验室开放基金(TKJ2023KL502015)

Space multi-target tracking method for space-based distributedpassive detection

Linhai JIANG1, Baichun GONG1,*, Chuankai LIU2,3, Yang YANG4, Renyong ZHANG5   

  1. 1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
    2. Beijing Aerospace Control Center, Beijing 100190, China
    3. Key Laboratory of Science and Technology on Space Flight Dynamics, Beijing 100190, China
    4. School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney 2052, Australia
    5. Technology and Engineering Center for Space Utilization, Chinese Academy of Science, Beijing 100094, China
  • Received:2023-05-30 Online:2024-07-25 Published:2024-08-07
  • Contact: Baichun GONG

摘要:

针对巨型星座群等空间非合作目标实时跟踪难题, 提出一种天基分布式协同无源探测的多目标跟踪方法。首先, 建立了地球非球形J2项摄动和大气阻力摄动条件下的轨道动力学模型, 并建立了星载的单位视线矢量测量模型。然后, 建立了基于势均衡概率假设密度滤波的多目标跟踪算法, 并采用高斯混合方法求得多维积分的近似封闭解, 降低算法的计算复杂度, 以解决星载实现问题。接着, 设计了多平台多目标跟踪交互的一致性信息融合方案, 引入标签进行目标区分, 减少不同平台之间信息传递与融合带来的计算匹配问题, 并使用一致性信息滤波进行信息融合。最后, 以某星座局部区域的15颗轨道相近的星座卫星作为跟踪目标, 对所提方法进行仿真实验验证。仿真结果表明所提方法有效, 跟踪性能比传统方法提升了约60%, 在协同构型不奇异情况下跟踪的位置误差在5 km以内。

关键词: 无源探测, 多目标跟踪, 一致性信息滤波, 分布式协同观测

Abstract:

In view of the real-time tracking problem of space non-cooperative spatial targets such as constellation groups of giant stars, a space-based distributed cooperative passive detection method for multi-target tracking is proposed. Firstly, a dynamic model of satellite orbit under the conditions of Earth's non-spherical J2 perturbation and atmospheric drag perturbation is established, along with a unit line-of-sight vector measurement model onboard. Then, a multi-target tracking algorithm based on cardinalized probability hypothesis density filtering is developed, and an approximate closed-form solution to multidimensional integrals is obtained using the Gaussian mixture method to reduce computational complexity and address onboard implementation issues. Furthermore, a consistency information fusion scheme for multi-platform multi-target tracking interaction is designed, incorporating labels for target discrimination to mitigate computational matching issues arising from information exchange and fusion between different platforms, and employing consistency information filtering scheme for information fusion. Finally, the proposed method is validated through simulation experiments using 15 orbitally proximate constellation satellites in a local region of a constellation as tracking targets. Simulation results demonstrate the effectiveness of the proposed method, with a tracking performance improvement of approximately 60% compared to traditional methods, and position tracking errors within 5 km under non-singular cooperative configurations.

Key words: passive detection, multi-target tracking, consensus-based information filtering, distributed collaborative observation

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