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Detection algorithms for ultrawideband foliage-penetration radar

机译:超宽带探叶雷达的检测算法

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Abstract: The Army Research Laboratory (ARL), as part of its mission- funded exploratory development program, has been evaluating the use of a low-frequency, ultra-wideband imaging radar to detect tactical vehicles concealed by foliage. An instrumentation-grade measurement system has been designed and implemented by ARL. Extensive testing of this radar over the preceding 18 months has led to the establishment of a significant and unique data base of radar imagery. We are currently using these data to develop target detection algorithms which can aid an operator in separating vehicles of interest from background. This paper provides early findings from the algorithm development effort. To date, our efforts have concentrated on identifying computationally simple strategies for canvassing large areas for likely target occurrences - i.e., prescreening of the imagery. Phenomenologically-sound features are being evaluated for discrimination capability. Performance assessments, in terms of receiver operating characteristics, detail detection capabilities at various false alarm rates.!11
机译:摘要:作为任务资助的探索性开发计划的一部分,陆军研究实验室(ARL)一直在评估低频超宽带成像雷达的使用,以探测被树叶掩盖的战术车辆。 ARL已设计并实施了仪器级测量系统。在过去的18个月中,对该雷达进行了广泛的测试,从而建立了重要而独特的雷达图像数据库。我们目前正在使用这些数据来开发目标检测算法,该算法可以帮助操作员将目标车辆从背景中分离出来。本文提供了算法开发工作中的早期发现。迄今为止,我们的工作集中在确定简单的计算策略,以便对可能的目标事件进行大面积布告(即图像的预筛选)。正在评估现象学上合理的特征的辨别能力。就接收器的工作特性而言,性能评估详细说明了各种误报率下的检测能力。!11

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