Xiaohua Tong, Yi Gao, Zhen Ye, Huan Xie, Peng Chen, Haibo Shi, Ziqi Liu, Xianglei Liu, Yusheng Xu, Rong Huang, Shijie Liu
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引用次数: 0
摘要
对远距离运动物体的位置和姿态信息进行动态测量是航空航天工程地面测试的常见需求。由于从远到近的运动和相机分辨率的限制,有必要使用多双目相机对不同距离进行分段观测。然而,实现精确、连续的位置和姿态估计是一项具有挑战性的任务。因此,本文提出了一种基于多双目视频测量系统的远距离运动动态监测技术。为了解决移动过程中图像尺度不断变化的问题,本文提出了一种圆形目标的尺度自适应跟踪方法。利用自适应加权最小二乘策略开发了关节段束调整(BA),以提高测量精度。通过对航天器交会对接的相对测量进行地面测试,验证了所提技术的可行性和可靠性。实验结果表明,所提出的技术可以获得运动物体的实际运动状态,定位精度为 3.2 毫米(均方根误差),可以为地面测试中的在轨测量系统提供可靠的第三方验证。与使用单个片段和视觉测量软件 PhotoModeler 的 BA 结果相比,精度分别提高了 45% 和 30%。
Dynamic measurement of a long-distance moving object using multi-binocular high-speed videogrammetry with adaptive-weighting bundle adjustment
The dynamic measurement of position and attitude information of a long-distance moving object is a common demand in ground testing of aerospace engineering. Due to the movement from far to near and the limitations of camera resolution, it is necessary to use multi-binocular cameras for segmented observation at different distances. However, achieving accurate and continuous position and attitude estimation is a challenging task. Therefore, this paper proposes a dynamic monitoring technique for long-distance movement based on a multi-binocular videogrammetric system. Aiming to solve the problem that the scale in images changes constantly during the moving process, a scale-adaptive tracking method of circular targets is presented. Bundle adjustment (BA) with joint segments using an adaptive-weighting least-squares strategy is developed to enhance the measurement accuracy. The feasibility and reliability of the proposed technique are validated by a ground testing of relative measurement for spacecraft rendezvous and docking. The experimental results indicate that the proposed technique can obtain the actual motion state of the moving object, with a positioning accuracy of 3.2 mm (root mean square error), which can provide a reliable third-party verification for on-orbit measurement systems in ground testing. Compared with the results of BA with individual segments and vision measurement software PhotoModeler, the accuracy is improved by 45% and 30%, respectively.