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Multi Sensors signature prediction workbench

机译:多传感器签名预测工作台

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Guidance of weapon systems relies on sensors to analyze targets signature. Defense weapon systems also need to detect then identify threats also using sensors. The sensors performance is very dependent on conditions e.g. time of day, atmospheric propagation, background ... Visible camera are very efficient for diurnal fine weather conditions, long wave infrared sensors for night vision, radar systems very efficient for seeing through atmosphere and/or foliage ... Besides, multi sensors systems, combining several collocated sensors with associated algorithms of fusion, provide better efficiency (typically for Enhanced Vision Systems). But these sophisticated systems are all the more difficult to conceive, assess and qualify. In that frame, multi sensors simulation is highly required. This paper focuses on multi sensors simulation tools. A first part makes a state of the Art of such simulation workbenches with a special focus on SE-Workbench. SE-Workbench is described with regards to infrared/EC1 sensors, millimeter waves sensors, active EO sensors and GNSS sensors. Then a general overview of simulation of targets and backgrounds signature objectives is presented, depending on the type of simulation required (parametric studies, open loop simulation, closed loop simulation, hybridization of SW simulation and HW ...). After the objective review, the paper presents some basic requirements for simulation implementation such as the deterministic behavior of simulation, mandatory to repeat it many times for parametric studies... Several technical topics are then discussed, such as the rendering technique (ray tracing vs. rasterization), the implementation (CPU vs. GP GPU) and the tradeoff between physical accuracy and performance of computation. Examples of results using SE-Workbench are showed and commented.
机译:武器系统的制导依靠传感器来分析目标特征。防御武器系统还需要使用传感器来检测然后识别威胁。传感器的性能非常取决于条件,例如一天中的时间,大气传播,背景...可见光摄像机对于白天的晴天天气非常有效,用于夜视的长波红外传感器,用于透视大气和/或树叶的雷达系统非常有效...此外,多传感器系统结合了多个并置的传感器和相关的融合算法,可以提供更高的效率(通常用于增强型视觉系统)。但是,这些复杂的系统更难以构思,评估和鉴定。在这种情况下,非常需要多传感器仿真。本文重点介绍多传感器仿真工具。第一部分介绍了此类模拟工作台的最新技术,特别关注SE-Workbench。 SE-Workbench针对红外/ EC1传感器,毫米波传感器,有源EO传感器和GNSS传感器进行了描述。然后,根据所需的模拟类型(参数研究,开环模拟,闭环模拟,SW模拟与HW的混合...),介绍了目标和背景签名目标模拟的一般概述。经过客观审查后,本文提出了一些模拟实施的基本要求,例如模拟的确定性行为,强制进行多次重复以进行参数研究...然后讨论了一些技术主题,例如渲染技术(光线跟踪与栅格化),实现(CPU与GP GPU)以及物理精度和计算性能之间的权衡。显示并评论了使用SE-Workbench的结果示例。

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