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Millimeter waves sensor modeling and simulation

机译:毫米波传感器建模和仿真

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摘要

Guidance of weapon systems relies on sensors to analyze targets signature. Defense weapon systems also need to detect then identify threats also using sensors. One important class of sensors are millimeter waves radar systems that are very efficient for seeing through atmosphere and/or foliage for example. This type of high frequency radar can produce high quality images with very tricky features such as dihedral & trihedral bright points, shadows and lay over effect. Besides, image quality is very dependent on the carrier velocity and trajectory. Such sensors systems are so complex that they need simulation to be tested. This paper presents a state of the Art of millimeter waves sensor models. A short presentation of asymptotic methods shows that physical optics support is mandatory to reach realistic results. SE-Workbench-RF tool is presented and typical examples of results are shown both in the frame of Synthetic Aperture Radar sensors and Real Beam Ground Mapping radars. 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-RF are showed and commented.
机译:武器系统的指导依赖于传感器分析目标签名。防御武器系统还需要检测然后使用传感器识别威胁。一类重要的传感器是毫米波的雷达系统,用于通过例如通过大气和/或叶子来看非常有效。这种类型的高频雷达可以产生高质量的图像,具有非常棘手的特征,如二对体和三面亮点,阴影并延续效果。此外,图像质量非常依赖于承载速度和轨迹。这种传感器系统如此复杂,以至于它们需要进行仿真。本文介绍了毫米波传感器型号的技术。渐近方法的简短介绍表明,物理光学支持是强制性的,以实现现实的结果。提出了SE-Workbench-RF工具,并且结果的典型示例在合成孔径雷达传感器和真实光束接地绘制雷达的框架中示出。然后讨论了几种技术主题,例如渲染技术(射线跟踪与光栅化),实现(CPU与GP GPU)和物理精度之间的权衡和计算。使用SE-Workbench-RF的结果的例子显示和评论。

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