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Ultrawideband radar target discrimination utilizing an advanced feature set

机译:利用高级功能集的超宽带雷达目标识别

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Abstract: The Army Research Laboratory, as part of its mission-funded applied research program, has been evaluating the utility of a low-frequency, ultra wideband imaging radar to detect tactical vehicles concealed by foliage. Measurement programs conducted at Aberdeen Proving Grounds and elsewhere have yielded a significant and unique database of extremely wideband and (in some cases) fully polarimetric data. Prior work has concentrated on developing computationally efficient methods to quickly canvass large quantities of data to identify likely target occurrences - often called `prescreening.' This paper reviews recent findings from our phenomenology/detection efforts. Included is a reformulated prescreener that has been trained and tested against a significantly larger data set than was used in the prior work. Also discussed are initial efforts aimed at the discrimination of targets from the difficult clutter remaining after prescreening. Performance assessments are included that detail detection rates versus false alarm levels.!16
机译:摘要:陆军研究实验室作为其任务资助的应用研究计划的一部分,一直在评估低频超宽带成像雷达在探测被树叶掩盖的战术车辆方面的实用性。在阿伯丁试验场和其他地方进行的测量程序已经产生了一个非常独特的数据库,该数据库包含极宽带和(在某些情况下)全极化数据。先前的工作集中在开发计算有效的方法上,以快速查看大量数据以识别可能的目标事件-通常称为“预筛查”。本文回顾了我们的现象学/检测工作的最新发现。其中包括经过重新配方的预筛选器,该筛选器已针对比以前的工作中使用的数据集大得多的数据集进行了培训和测试。还讨论了旨在将目标与预筛分后残留的困难杂物区分开的初步努力。包括性能评估,详细列出了检出率与错误警报级别之间的差异。!16

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