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    • 摘要: 实际自适应光学控制系统中存在的时间延迟,导致校正器生成的校正面形与实际的波前畸变不匹配,产生校正滞后误差。基于大气冻结湍流假设,提出了一种基于运动估计的波前畸变预测方法,来补偿时间延迟带来的影响。方法具体采用模板匹配算法,根据参考帧和当前帧的波前复原图像进行大气湍流运动方向估计,然后对当前帧进行移动处理来实现对下一帧图像的预测。通过采用不同采样频率、不同横向风速度的仿真数据对比,评估预测方法的适用范围,讨论回溯帧数对预测效果的影响。也与采用最小递归二乘(RLS)模式预测方法的预测效果进行比较。仿真结果显示,在波前复原图像变化趋势较为明显的情况下,即横向风对大气湍流变化影响占主导地位时,方法表现更好,使得在天气较为恶劣的情况下仍能保持更佳的预测效果。最后使用实际天狼星观测数据对预测方法进行验证,整体仍保持预测效果。

       

      Abstract: In the actual adaptive optics control system, the time delay causes the mismatch between the correction profile generated by the corrector and the actual wavefront distortion, which leads to correction lag error. Under the atmospheric frozen flow turbulence assumption, a wavefront distortion prediction method based on motion estimation is proposed to compensate for the time delay. The template matching algorithm is used to estimate the atmospheric turbulence motion direction, according to the wavefront restored images of the reference frame and the current frame, and then the current frame is moved to predict the next frame. The prediction method applicability is evaluated, and the influence of backtracking frames on the prediction effect is discussed by comparing the simulation data of different sampling frequencies and different transverse wind speeds. The residual error is calculated with the template matching algorithm and the least recursive squares (RLS) algorithm. The simulation results show that the method performs better when the variation tendency of wavefront restored images is obvious. Therefore, the prediction effect can be maintained better in severe conditions. Finally, the prediction method is verified by using the actual observation data of Sirius, and the algorithm still keeps the prediction effect.