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首页> 外文期刊>Journal of guidance, control, and dynamics >Robust Autonomous Small-Body Shape Reconstruction and Relative Navigation Using Range Images
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Robust Autonomous Small-Body Shape Reconstruction and Relative Navigation Using Range Images

机译：使用距离图像进行鲁棒的自主小体形状重构和相对导航

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摘要

This paper proposes an algorithm relying on range images to reconstruct the shape model of the orbited object, train an uncertainty model representative of shape reconstruction inaccuracies and sensor noise using a maximum-likelihood approach combined with a particle-swarm optimizer, and perform model-based relative navigation by comparing range measurements from the onboard shape model to those provided by a light-detection-and-ranging sensor. The presented algorithm yielded a satisfying estimate of the shape model of interest (point-cloud-to-shape RMS residuals of 0.497m), along with a consistent range error metric that was trained by means of likelihood maximization over the measured range residuals. The reconstructed shape model of asteroid Itokawa and its associated uncertainty metric were used by an iterated extended Kalman filter for navigation. The filter returned an estimate of the spacecraft state and asteroid attitude that was consistent with the covariance envelopes, despite the defects in the reconstructed shape.
机译：本文提出了一种基于距离图像的算法来重建轨道物体的形状模型，使用最大似然方法结合粒子群优化器训练表示形状重建不精确度和传感器噪声的不确定性模型，并执行基于模型的算法相对导航，方法是将机载形状模型的距离测量值与光检测范围传感器提供的距离值进行比较。提出的算法对感兴趣的形状模型（点云到形状RMS残差为0.497m）以及一致的范围误差度量进行了令人满意的估计，该度量通过对测得的范围残差进行似然最大化来训练。迭代的扩展卡尔曼滤波器将小行星线川的形状模型及其相关的不确定性度量标准用于导航。尽管重建形状有缺陷，但过滤器仍返回与协方差包络线一致的航天器状态和小行星姿态的估计值。

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  • 来源
    《Journal of guidance, control, and dynamics》 |2019年第7期|1473-1488|共16页
  • 作者

    Bercovici Benjamin; McMahon Jay W.;

  • 作者单位

    Univ Colorado, Dept Aerosp Engn Sci, Boulder, CO 80309 USA|AIAA, Reston, VA 20191 USA;

    Univ Colorado, Dept Aerosp Engn Sci, Boulder, CO 80309 USA|AIAA, Reston, VA 20191 USA;

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