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  • AGI STK EOIR对地精细成像


    AGI STK EOIR对地精细成像,测试通过。

    利用STK相关设置进行精细对地成像,评估传感器成像效果。 成像效果如上图所示。结合MATLAB代码进行处理,可以获得高分辨率的地表图像。该图像示例是一亿像素的图片局部成像效果。EOIR传感器设置分辨率为512×512。在STK11.6.0、win10环境下测试通过。需要STK、MATLAB和EOIR模块。

    STK EOIR provides computer automation support for people who specify, develop, or operate systems that include electro-optical/infrared sensors. STK EOIR’s physics-based models rapidly and interactively calculate medium-fidelity results, allowing users to quickly explore a wide set of possible alternatives to discover a best solution to the problem at hand. As the best solutions are determined, the user can, as necessary, select higher fidelity models within STK EOIR or revert to other, more traditional phenomenology codes within a more restricted solution space.

    STK EOIR provides the following advantages:

     STK EOIR incorporates all necessary components for modeling sensor-based systems into a single program, saving users the task of compiling results from separately operated programs.

     A single, trained user can operate STK EOIR in all its aspects. Teams of subject experts are not required.

     STK EOIR enables sensor modeling to take place over an incredible diversity of applications and range of scales—serving needs ranging from Ballistic Missile Defense to Space Situational Awareness to Civil Space Exploration anywhere in the Solar System.

     As a maintained COTS product, the development costs are distributed across all users.

    EOIR

    • The ability to use custom target signatures has been added for use in your EOIR analysis. You can import modeled or database signatures, including laser beam signatures, into STK via external files and perform various analysis tasks, such as:
      • Illuminating of space objects with lasers.
      • Docking sensors and laser communications.
      • Simulating complex system interactions of EMR.
    • The EOIR default rendering mode was optimized to improve the speed for generating both synthetic scenes and sensor-to-target metrics.
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  • 原文地址:https://blog.csdn.net/johnliuyuan/article/details/125527769
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