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New method for target identification in a foliage environment using selected bispectra and chaos particle swarm optimisation-based support vector machine

机译:使用选定的双谱和基于混沌粒子群优化的支持向量机识别树叶环境中目标的新方法

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摘要

In this study, a novel method for target identification in a foliage environment is presented. This method is based on the ultra wideband (UWB) wireless sensor networks (WSNs) model, and the foliage environment is specially considered. The data used to identify the targets are derived from the received signal waveform, so most existing transceivers can be exploited as detecting sensors, which leads to a potential low-cost way to identify targets during the normal communications within the WSNs under foliage environment. The selected bispectra algorithm is applied to extract the feature vector, and chaos particle swarm optimisation-based support vector machine is used as the target classifier. Experiments with real-world data samples indicate that this method has an excellent classification performance in a foliage environment. Moreover, this method shows potential for online training.
机译:在这项研究中,提出了一种在树叶环境中进行目标识别的新方法。此方法基于超宽带(UWB)无线传感器网络(WSN)模型,并且特别考虑了树叶环境。用于识别目标的数据是从接收到的信号波形中得出的,因此大多数现有的收发器都可以用作检测传感器,这导致了在树叶环境下的WSN进行常规通信期间,潜在的低成本方法来识别目标。应用选择的双谱算法提取特征向量,将基于混沌粒子群优化的支持向量机作为目标分类器。实际数据样本的实验表明,该方法在枝叶环境中具有出色的分类性能。而且,这种方法显示了在线培训的潜力。

著录项

  • 来源
    《Signal Processing, IET 》 |2014年第1期| 76-84| 共9页
  • 作者

    Minglei You; Ting Jiang;

  • 作者单位

    Key Lab. of Universal Wireless Commun., Beijing Univ. of Posts & Telecommun., Beijing, China|c|;

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  • 正文语种 eng
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