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Integration of optomechanical system models with DIRSIG

机译:Dirsig的光学机械系统模型集成

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Stray light, any unwanted radiation that reaches a focal plane, presents a significant challenge for both airborne and satellite remote sensing systems by reducing image contrast, creating false signals or obscuring faint ones, and ultimately degrading radiometric accuracy. These detrimental effects can have a profound impact on the usability of collected data, which must be radiometrically calibrated to be useful for scientific applications. Understanding the full impact of stray light on data scientific utility is of particular concern for lower cost, more compact satellite systems which inherently provide fewer opportunities for stray light control. To address these concerns, we present a general methodology for integrating an optomechanical system model with the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. The results reported in this paper describe the collection of necessary raytrace data from an optomechanical system model (in this case, using FRED Optical Engineering Software), and also include the initial demonstration of the integration method by imaging DIRSIG test scenes. By integrating a high-fidelity optomechanical system model with a physics-driven, synthetic image generation model like DIRSIG, we are now able to explore system trade studies and conduct sensitivity analyses on parameters of interest, including those that influence stray light, by analyzing their effects on realistic test scenes. This new capability further aids in demonstrating the quantitative linkage between system trade studies and impact to scientific users, which will enhance the writing of system requirements.
机译:杂散光,到达焦平面的任何不需要的辐射,通过减少图像对比度,产生假信号或模糊微弱的辐射,并最终降低辐射度精度,对空中和卫星遥感系统进行了重大挑战。这些有害效果可以对收集数据的可用性产生深远的影响,这必须是无线化校准的,以对科学应用有用。了解杂散光对数据科学效用的全部影响特别关注较低的成本,更紧凑的卫星系统,该系统本身提供了更少的杂散光控制机会。为了解决这些问题,我们提出了一种用于将光机械系统模型与数字成像和遥感图像生成(DIRSIG)模型集成的一般方法。本文报告的结果描述了来自光学机械系统模型的必要途径数据的集合(在这种情况下,使用Fred光学工程软件),并且还包括通过成像DirSIG测试场景来初始演示。通过将高保真光机械系统模型与物理驱动的合成图像生成模型相结合,我们现在能够探索系统贸易研究,并对感兴趣的参数进行敏感性分析,包括通过分析它们的影响对现实测试场景的影响。这种新能力进一步涉及在系统贸易研究和对科学用户的影响方面表现出定量联系,这将提高系统要求的写作。

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