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Development of fast tracking algorithm using nearest neighbor star search approach

机译：利用最近邻恒星搜索法开发快速跟踪算法

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New tracking algorithm based on the nearest neighbor star search approach is proposed for fast star identification. In order to improve the performance of tracking, this algorithm is composed of two parts. One is a searching part of unknown stars in the field of view (FOV) using nearest neighbor star search approach. The feature of this method is that each star has connections with some adjacent stars. Unknown stars can be identified by tracing the nearest star from the previously recognized star with reference to the star catalog. Star neighborhood information is a list of neighbor stars in the order of closeness and included in the catalog. The other is a predicting part of position of stars on the current image frame. Star position can be predicted from satellite angular velocity and previous attitude information. In this technique, angular velocity is estimated by the last two captured images without gyroscope observation. Most of the stars in the FOV are tracked properly by matching star centroid position on the captured image with the predicted star position. Star trackers for micro-satellite developed by Tohoku University so far had only lost-in-space attitude determination algorithm, whose operation frequency was limited down to 1 Hz. It is expected that the above mentioned star identification method enables improvement both in reliability and operational frequency. This algorithm was evaluated in PC simulation. The results show that attitude determination can be carried out over twenty times faster compared to the conventional method. Hence, it is illustrated that the efficiency of star identification is improved by these approaches.
机译：基于最近邻邻星搜索方法的新型跟踪算法，用于快速明星识别。为了提高跟踪的性能，该算法由两部分组成。一个是使用最近的邻居星形搜索方法在视野（FOV）中的未知恒星的搜索部分。这种方法的特征是每个星都与一些相邻的恒星有连接。可以通过参考星目录跟踪先前识别的明星来识别未知的恒星。 STAR邻里信息是邻近的邻居星列表，并包含在目录中。另一个是预测当前图像帧上的星星位置的一部分。可以从卫星角速度和以前的姿态信息预测星球。在该技术中，在没有陀螺仪观察的情况下，最后两个捕获的图像估计角速度。通过将捕获图像与预测的星位置匹配在捕获的图像上匹配星形位置，正确地跟踪FOV中的大多数恒星。到目前为止由Tohoku University开发的微卫星的星形跟踪器只有空间丢失的姿态确定算法，其操作频率限制为1 Hz。预计上述明星识别方法可以在可靠性和操作频率方面改进。在PC仿真中评估了该算法。结果表明，与传统方法相比，姿态测定可以更快地进行二十倍。因此，说明通过这些方法改善了星识别的效率。

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