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阐述了高动态星敏感器星图的特点,指出了目前星跟踪方法的不足。针对这些不足,提出了一种基于卡尔曼预测的高动态星跟踪方法。根据高动态星敏感器运动特性,建立了星体目标在图像坐标系下运动模型,根据星体运动模型,对卡尔曼滤波器进行了自适应修正。利用经自适应修正的卡尔曼滤波器预测出参考星位置,再利用临星逼近法进行跟踪匹配。最后给出了利用上述方法进行星体位置预测及星跟踪结果。实验结果表明,在5(°)/s动态条件下星体位置预测偏差小于5像素,星跟踪成功率高于95%,并且载体动态特性的变化对星体跟踪成功率影响较小。
The characteristics of star map of high dynamic star sensor are expounded, and the deficiency of current star tracking method is pointed out. Aiming at these shortcomings, a high dynamic star tracking method based on Kalman prediction is proposed. According to the motion characteristics of the high-dynamic star sensor, the motion model of the star target in the image coordinate system is established, and the Kalman filter is adaptively modified according to the star motion model. The Kalman filter with adaptive correction is used to predict the position of the reference star, and then the tracking matching is made by the method of star approaching. Finally, the method of star position prediction and star tracking is given. The experimental results show that the prediction error of the position of the stars is less than 5 pixels under the dynamic conditions of 5 (°) / s, the success rate of the star tracking is higher than 95%, and the change of the dynamic characteristics of the carriers has little effect on the success rate of the stars tracking.