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作 者:李葆华[1] 马衍宇[1] 刘睿[1] 王常虹[1]
机构地区:[1]哈尔滨工业大学空间控制与惯性技术研究中心,黑龙江哈尔滨150001
出 处:《光学精密工程》2009年第1期191-195,共5页Optics and Precision Engineering
基 金:国家863高技术研究发展计划资助项目(No.2005AA745060);十一五共性技术资助项目(No.51320050301);哈尔滨工业大学博士后建设资助项目
摘 要:提出了一种自主预测视场内未知恒星星像质心算法。该算法采用星跟踪算法来提取视场内已知恒星星像坐标。根据已知恒星信息从主星表中搜索视场内所有未知恒星,并采用这些信息预测所有未知恒星的理想像平面中心,从以这些预测的理想坐标为中心的范围内提取相应的实际星像坐标。同时采用已知恒星来验证未知恒星星像坐标。最后,对该算法进行了外场观星测试。实验结果表明:该方法提取未知恒星星像坐标时,扫描星图的像元只有局部提取星像算法的0.12%,所以进一步提高了数据更新率。An autonomous predictive centroiding algorithm of unmatched stars is presented in this paper to obtain the real star centroidings of identified stars with star tracking algorithm. All the un matched stars within Field of View(FOV) are searched from a guide star catalogue according to identified stars. Then, these ideal centroidings of unmatched stars are calculated through these identified stars. The algorithm can obtain the real centroidings of unmatched stars within some threshold scan windows of star image and can identify the centroidings of unmatched stars through the identified stars within FOV,so that recognition performance is improved. The algorithm is successfully demonstrated by real space experiments, experimental results show that the number of pixels of scanning star image by the proposed algorithm is only 0.12% of that by local obtaining star location algorithm,when unrecognized star locations are captured. The conclusions reported here prove that proposed method can improve the update rate of data.
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