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空间巡天相机稳像系统的控制精度要求高,对导航星传感器提出了更高的要求。为提高导航星传感器的精度和带宽,提出了一种采用预测开窗和Kalman滤波相结合的星点定位方法。利用陀螺测量的三轴角速度信息,推导建立星点粗位置预测方程,得到星点的粗位置,在CMOS探测器上以预测点为中心的较小邻域范围内开窗,可提高运算速度。利用Kalman滤波算法对星点位置进行校正,最终得到高精度的星点位置。仿真实验结果表明,相比于传统的质心法,平均每帧图像处理时间从59ms减少到27ms,定位结果的标准差从0.1pixel减小到0.04pixel。提出的方法是一条提高星点定位运算速度和精度的有效途径,可为我国巡天相机导航星系统的研制提供一定参考。
Space surveillance camera stabilization system of high precision control of the navigation satellite sensors put forward higher requirements. In order to improve the accuracy and bandwidth of the navigation satellite sensor, a new method of positioning the star using the combination of predictive windowing and Kalman filtering is proposed. The three-axis angular velocity information of the gyroscope is used to derive the prediction equation for the rough position of the star point. The rough position of the star point is obtained. In the CMOS detector, the window is opened in the smaller neighborhood with the prediction point as the center, which increases the calculation speed. The Kalman filter algorithm is used to correct the position of the star point, and finally the high-precision star point position is obtained. The simulation results show that the average processing time per frame is reduced from 59 ms to 27 ms compared with the traditional centroid method, and the standard deviation of positioning results is reduced from 0.1 pixel to 0.04 pixel. The proposed method is an effective way to improve the speed and accuracy of satellite positioning, which can provide some reference for the development of satellite navigation system in China.