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Integrated approach for automatic target recognition using a network of collaborative sensors

机译:使用协作传感器网络自动目标识别的集成方法

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摘要

We introduce what is believed to be a novel concept by which several sensors with automatic target recognition (ATR) capability collaborate to recognize objects. Such an approach would be suitable for netted systems in which the sensors and platforms can coordinate to optimize end-to-end performance. We use correlation filtering techniques to facilitate the development of the concept, although other ATR algorithms may be easily substituted. Essentially, a self-configuring geometry of netted platforms is proposed that positions the sensors optimally with respect to each other, and takes into account the interactions among the sensor, the recognition algorithms, and the classes of the objects to be recognized. We show how such a paradigm optimizes overall performance, and illustrate the collaborative ATR scheme for recognizing targets in synthetic aperture radar imagery by using viewing position as a sensor parameter.
机译:我们介绍了被认为是一个新颖的概念,通过该概念,几个具有自动目标识别(ATR)功能的传感器可以协作来识别对象。这种方法将适用于联网的系统,其中传感器和平台可以协调以优化端到端性能。尽管可以使用其他ATR算法轻松替换,但我们使用相关过滤技术来促进概念的发展。本质上,提出了一种网状平台的自配置几何结构,该结构可将传感器相对于彼此进行最佳定位,并考虑到传感器,识别算法和要识别的对象类别之间的相互作用。我们将展示这种范例如何优化整体性能,并说明通过使用观察位置作为传感器参数来识别合成孔径雷达图像中目标的协作式ATR方案。

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