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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
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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
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Journal Article
New method for target identification in a foliage environment using selected bispectra and chaos particle swarm optimisation-based support vector machine
2014
Overview
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.
Publisher
The Institution of Engineering and Technology,Institution of Engineering and Technology,John Wiley & Sons, Inc
Subject
/ chaos
/ chaos particle swarm optimisation‐based support vector machine
/ Detection, estimation, filtering, equalization, prediction
/ Exact sciences and technology
/ Foliage
/ geophysical signal processing
/ Information, signal and communications theory
/ Signal and communications theory
/ Signal representation. Spectral analysis
/ Telecommunications and information theory
/ ultra wideband wireless sensor network
/ UWB
/ WSN
