RANSAC算法在空间目标光电跟踪中的应用研究

基于光电跟踪设备对空间目标进行跟踪测量时，由于电磁干扰、云层遮挡或者地影等因素的影响，造成空间目标成像在设备视场中无法提取，严重时甚至导致系统闭环跟踪不能平稳进行。此时可以采用理论引导的方式，利用预测轨迹继续进行跟踪搜索。本文将广泛用于计算机视觉领域特征提取的随机抽样一致性(RANSAC)算法引入轨迹预测，并根据观测数据分布的特点进行改进提出WRANSAC算法，用于实时处理有限的历史观测数据，进行轨迹预测。引入该算法后，在对空间目标轨迹预测时，对历史观测数据的容错能力提高，对模型的敏感性降低，预测结果的准确性和鲁棒性远远优于最小二乘法。通过对比预测轨迹和实际轨迹，证明了该算法的有效性。

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关键词：

参数估计; 随机抽样一致性; 损失函数; 空间目标; 轨迹预测

基金项目：

中国科学院空间科学背景型号项目(XDA15020400)

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引用本文：严灵杰, 黄永梅, 张涯辉, 等. RANSAC算法在空间目标光电跟踪中的应用研究[J]. 光电工程, 2019, 46(11): 180540.

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2019年第11期

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