时序平滑多尺度叠加动态红外云场景仿真

Dynamic infrared cloud scene simulation based on time series smoothing multiscale superposition

  • 摘要: 天基红外观测场景中云场景具有几何结构动态变化复杂、尺度变化随机、辐射动态变化不确定的特点且与天基动态探测链路耦合,对系统探测效能造成极大影响。因此,开展云场景仿真方法研究对天基红外光学卫星系统设计具有非常重要的意义。针对传统仿真方法在大尺度动态云图像仿真应用中计算效率低、占用内存大的问题,提出了一种基于时序平滑多尺度叠加方法的动态云图像仿真方法,在基于多尺度叠加算法进行云层整体位置移动仿真的基础上,利用帧间插值的方法实现动态云层形状结构变化,计算效率提高10倍以上,真实模拟云场景的整体移动与内部变化,实现大尺度动态云图像的仿真。

     

    Abstract: The cloud scene in the space-based infrared observation scene has the characteristics of geometric structure dynamic change, scale dynamic change, radiation dynamic change and is coupled with the space-based dynamic detection link, which will have a great impact on the detection efficiency of the system. Therefore, it is very important to carry out research on cloud scene simulation methods for the design of space-based infrared optical satellite systems. This paper proposes a dynamic cloud image simulation method based on the time series smoothing multiscale superposition method to solve the problems of low computational efficiency and large memory usage of traditional simulation methods in large-scale dynamic cloud image simulation applications. The interframe interpolation method is used to realize the change in the shape and structure of the dynamic cloud layer, which improves the computational efficiency by more than 10 times. Realistic simulation of the overall structural change in the position and shape of the clouds realizes the simulation of large-scale dynamic cloud images.

     

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