Target identification in foliage environment using selected bispectra and Extreme Learning Machine

Minglei You, Ting Jiang
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引用次数: 3

Abstract

In this paper, a novel method of target identification in foliage environment is presented. This method takes the received signal waveforms to identify the targets between the communication transceivers, which are measured by Ultra WideBand (UWB) Impulse Radio (IR) equipment under foliage environment. In this way, most existing UWB-IR transceivers can be exploited as detecting radar sensors, which leads to a potential low-cost way to identify targets under foliage environment. The selected bispectra algorithm is applied to extract the feature vector, and Extreme Learning Machine is used as the target classifier. Experiments with real-world data samples indicate that this method has an excellent classification performance in foliage environment.
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基于选择性双光谱和极限学习机的树叶环境目标识别
提出了一种树叶环境下目标识别的新方法。该方法利用接收到的信号波形来识别通信收发器之间的目标,并利用超宽带脉冲无线电(UWB)设备在树叶环境下进行测量。通过这种方式,现有的大多数UWB-IR收发器都可以被用作探测雷达传感器,从而为在树叶环境下识别目标提供了一种潜在的低成本方法。采用选择的双谱算法提取特征向量,使用极限学习机作为目标分类器。实际数据样本的实验表明,该方法在树叶环境下具有良好的分类性能。
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