Research Center of Satellite Technology, Harbin Institute of Technology, Harbin 150080, China.
Sensors (Basel). 2018 Aug 13;18(8):2662. doi: 10.3390/s18082662.
Under dynamic conditions, motion blur is introduced to star images obtained by a star sensor. Motion blur affects the accuracy of the star centroid extraction and the identification of stars, further reducing the performance of the star sensor. In this paper, a star image restoration algorithm is investigated to reduce the effect of motion blur on the star image. The algorithm includes a blur kernel calculation aided by a MEMS gyroscope, blur kernel correction based on the structure of the star strip, and a star image reconstruction method based on scaled gradient projection (SGP). Firstly, the motion trajectory of the star spot is deduced, aided by a MEMS gyroscope. Moreover, the initial blur kernel is calculated by using the motion trajectory. Then, the structure information star strip is extracted by Delaunay triangulation. Based on the structure information, a blur kernel correction method is presented by utilizing the preconditioned conjugate gradient interior point algorithm to reduce the influence of bias and installation deviation of the gyroscope on the blur kernel. Furthermore, a speed-up image reconstruction method based on SGP is presented for time-saving. Simulated experiment results demonstrate that both the blur kernel determination and star image reconstruction methods are effective. A real star image experiment shows that the accuracy of the star centroid extraction and the number of identified stars increase after restoration by the proposed algorithm.
在动态条件下，星敏感器获得的星像会引入运动模糊。运动模糊会影响星点质心提取和星识别的准确性，从而降低星敏感器的性能。本文研究了一种星像复原算法，以降低运动模糊对星像的影响。该算法包括基于微机电系统（MEMS）陀螺仪辅助的模糊核计算、基于星条纹结构的模糊核校正以及基于尺度梯度投影（SGP）的星像重建方法。首先，利用 MEMS 陀螺仪推导星点的运动轨迹，并计算初始模糊核。然后，通过 Delaunay 三角剖分提取结构信息星条纹。基于结构信息，利用预处理共轭梯度内点算法提出了一种模糊核校正方法，以减小陀螺仪的偏差和安装误差对模糊核的影响。此外，还提出了一种基于 SGP 的加速图像重建方法，以节省时间。仿真实验结果表明，模糊核确定和星像重建方法均有效。真实星像实验表明，经该算法复原后，星点质心提取的精度和识别的星点数增加。
