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首页> 外文期刊>IEEE Transactions on Aerospace and Electronic Systems >Recursive mode star identification algorithms
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Recursive mode star identification algorithms

机译：递归模式恒星识别算法

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摘要

Star identification can be accomplished by several different available algorithms that identify the stars observed by a star tracker. However, efficiency and reliability remain key issues and the availability of new active pixel cameras requires new approaches. Two novel algorithms for recursive mode star identification are presented here. The first approach is derived by the spherical polygon search (SP-search) algorithm, it was used to access all the cataloged stars observed by the sensor field-of-view (FOV) and recursively add/remove candidate cataloged stars according to the predicted image motion induced by camera attitude dynamics. Star identification is then accomplished by a star pattern matching technique which identifies the observed stars in the reference catalog. The second method uses star neighborhood information and a catalog neighborhood pointer matrix to access the star catalog. In the recursive star identification process, and under the assumption of "slow" attitude dynamics, only the stars in the neighborhood of previously identified stars are considered for star identification in the succeeding frames. Numerical tests are performed to validate the absolute and relative efficiency of the proposed methods.
机译：恒星识别可以通过几种不同的可用算法来完成，这些算法可以识别恒星跟踪器观测到的恒星。然而，效率和可靠性仍然是关键问题，并且新的有源像素相机的可用性需要新的方法。这里介绍了两种新颖的递归模式恒星识别算法。第一种方法是通过球形多边形搜索（SP-search）算法得出的，用于访问传感器视场（FOV）观测到的所有目录星，并根据预测结果递归地添加/删除候选目录星相机姿态动力学引起的图像运动。然后，通过星形匹配技术完成恒星识别，该技术可识别参考目录中的观测恒星。第二种方法使用星形邻域信息和目录邻域指针矩阵来访问星形目录。在递归恒星识别过程中，在“慢速”姿态动力学的假设下，只有先前识别的恒星附近的恒星才被考虑用于后续帧中的恒星识别。进行数值测试以验证所提出方法的绝对和相对效率。

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