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Diffusion-based cooperative space object tracking

机译：基于扩散的协同空间目标跟踪

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摘要

We propose the diffusion-based enhanced covariance intersection cooperative space object tracking (DeCiSpOT) filter. The main advantage of the proposed DeCiSpOT algorithm is that it can balance the computational complexity and communication requirements between different sensors as well as improve track accuracy when measurements do not exist or are of low accuracy. Instead of using the standard covariance intersection in the diffusion step, the enhanced diffusion strategy integrates the 0-1 weighting covariance intersection strategy and the iterative covariance intersection strategy. The proposed DeCiSpOT algorithm also uses the global nearest neighbor and probabilistic data association for multiple space object tracking. Two typical scenarios including cooperative single and multiple space object tracking are used to demonstrate the performance of the proposed DeCiSpOT filter. Using simulated ground-based electro-optical (EO) measurements for multiple resident space objects and multiple distributed EO sensors, the DeCiSpOT archived results comparable to an optimal centralized approach. The results demonstrate that the DeCiSpOT is effective for space object tracking problem with results close to the optimal centralized cubature Kalman filter. distributed tracking; space object; covariance intersection; Kalman filter; diffusion.
机译：我们提出了基于扩散的增强协方差相交合作空间目标跟踪（DeCiSpOT）滤波器。提出的DeCiSpOT算法的主要优点是，它可以平衡计算复杂性和不同传感器之间的通信要求，并在不存在测量或精度较低的情况下提高跟踪精度。代替在扩散步骤中使用标准协方差交集，增强型扩散策略将0-1加权协方差交集策略与迭代协方差交集策略集成在一起。提出的DeCiSpOT算法还将全局最近邻居和概率数据关联用于多个空间物体跟踪。两种典型的场景，包括合作的单个和多个空间物体跟踪，被用来证明所提出的DeCiSpOT滤波器的性能。通过对多个驻留空间物体和多个分布式EO传感器使用模拟的地面电光（EO）测量，DeCiSpOT存档的结果可与最佳集中式方法媲美。结果表明，DeCiSpOT对空间物体跟踪问题有效，其结果接近于最佳集中式库尔曼卡尔曼滤波器。分布式跟踪；空间物体协方差交点卡尔曼滤波器扩散。

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  • 来源
    《Optical engineering》 |2019年第4期|041607.1-041607.11|共11页
  • 作者

    Bin Jia; Khanh Pham; Erik Blasch; Genshe Chen; Dan Shen;

  • 作者单位

    Intelligent Fusion Technology, Inc., Germantown, Maryland, United States;

    Air Force Research Lab, Kirtland Air Force Base, Albuquerque, New Mexico, United States;

    Air Force Office of Scientific Research, Arlington, Virginia, United States;

    Intelligent Fusion Technology, Inc., Germantown, Maryland, United States;

    Intelligent Fusion Technology, Inc., Germantown, Maryland, United States;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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