卫星观测火箭尾喷焰红外动态场景生成研究

建立了一种星载吸收波段红外传感器连续观测助推段火箭飞行的场景生成模型。提出了一种基于神经网络生成MODIS数据中第22、23波段高分辨率地表发射率图像的方法，生成了分辨率达到百米量级的地表发射率图像，并利用谱段关联计算了4.18~4.5 μm的地表光谱发射率；同时采用Runge-Kutta法生成火箭助推段的飞行轨迹，利用LOS方法计算尾喷焰气体的辐射传输，生成火箭尾喷焰图像。建立了尾喷焰、地表点和传感器的几何关系，对尾喷焰和背景投影成像，合成了卫星观测火箭尾喷焰的动态场景。对辐亮度图像序列进行分析发现，地面背景的辐亮度得到了压制，同时结合轨迹数据对不同时刻的目标辐亮度对比度和所占像元数进行了分析。此外，分析了不同场景下尾喷焰总辐射强度曲线的差异。结果表明，场景生成方法准确可靠，可为基于卫星图像序列的目标检测跟踪等研究提供数据基础和目标特性支撑。

Infrared dynamic scene generation of rocket plume observed by satellite

A dynamic scene generation model for continuous observation of rocket in boost phase by infrared sensor in absorption band of satellite was established. A method of generating high-resolution surface emissivity images at band 22 and 23 of MODIS data based on neural networks was proposed. According to the proposed method, surface emissivity images with resolution of 100 meters were generated. Spectral emissivity of 4.18-4.5 μm was calculated by spectral correlation method; flight trajectories of rocket in boost phase were generated by Runge-Kutta method, and plume radiation transmission was calculated by LOS method to generate rocket plume image. The geometric relationship among rocket plume, surface points and the sensor on satellite was established. The plume and background were projected and imaged, and the dynamic scene of the rocket plume observed by the satellite was synthesized. By analyzing the radiance image sequences, it was found that radiances of the ground background was suppressed. At the same time, the target radiance contrast and the number of pixels occupied at different times were analyzed combined with the trajectory data. Furthermore, the difference of total radiation intensity curve of plume in different scenes was analyzed. The results show that the scene generation method is accurate and reliable, which can provide data basis and target characteristics support for target detection and tracking research based on images observed by satellite.