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59 ms减少到27 ms，定位结果的标准差从0.1 pixel减小到0.04 pixel。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 survey camera image stabilization system demands high control accuracy and puts forward higher requirements on the guide star sensor. In order to improve the accuracy and bandwidth of guide star sensor, star spot location method combining prediction windowing and Kalman filter is presented. Using gyros to measure three-axis angular rate information, and establishing a prediction equation for the rough position of the star spot, the rough position of star spot is obtained. Windowing in a small neighborhood of the predicted spot on the CMOS detector can improve the operation speed. Using Kalman filter algorithm to correct the position of the star spot, the accurate position of star spot is finally obtained. Simulation results show that compared with traditional centroid method, image processing time per frame is reduced from 59 ms to 27 ms, and the standard deviation of star location result is reduced from 0.1 pixel to 0.04 pixel. The proposed method is an effective way to improve the speed and accuracy of the star spot location, providing certain value for the development of China′s space survey camera.