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Smart weapons operability enhancement synthetic scene generation process

机译:智能武器可操作性增强综合场景生成过程

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Abstract: The smart weapons operability enhancement (SWOE) program has developed a synthetic scene generation process that incorporates formal experimental design, random sampling procedures, data collection methods, physics models, and numerically repeatable validation procedures. The SWOE synthetic scene generation procedure uses an assemblage of measurements, static and dynamic information databases, thermal and radiance models, and rendering techniques to simulate a wide range of environmental conditions. The models provide a spatial and spectral agility that permits the simulation of a wide range of sensor systems for varied environmental conditions. Comprehensive validation efforts have been conducted for two locations: Grayling, Michigan and Yuma, Arizona, and for two spectral bands: shortwave (3 - 5 $mu@m) and longwave (8 - 12 $mu@m) IR. The intended use of the validated SWOE process is synthetic battlefield scene generation. The users of the SWOE process are the smart weapons system designers, developers, testers and evaluators, including developers of automatic target recognition algorithms and techniques. !9
机译:摘要:智能武器可操作性增强(SWOE)程序已经开发了一种综合场景生成过程,该过程结合了正式的实验设计,随机抽样程序,数据收集方法,物理模型和数值可重复的验证程序。 SWOE合成场景生成过程使用测量值,静态和动态信息数据库,热和辐射模型以及渲染技术的组合来模拟各种环境条件。这些模型提供了空间和光谱敏捷性,可以模拟各种传感器系统以适应各种环境条件。已经针对两个地点进行了全面的验证工作:密歇根州的格雷林和亚利桑那州的尤马市,以及两个光谱带:短波(3-5μm@ m)和长波(8-12μm@ m)IR。经过验证的SWOE流程的预期用途是合成战场场景生成。 SWOE流程的用户是智能武器系统的设计人员,开发人员,测试人员和评估人员,包括自动目标识别算法和技术的开发人员。 !9

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