Open AccessNew method for target identification in a foliage environment using selected bispectra and chaos particle swarm optimisation‐based support vector machine
Author(s) -
You Minglei,
Jiang Ting
Publication year - 2014
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
eISSN - 1751-9683
pISSN - 1751-9675
DOI - 10.1049/iet-spr.2012.0389
Subject(s) - chaos (operating system) , particle swarm optimization , identification (biology) , support vector machine , computer science , artificial intelligence , pattern recognition (psychology) , control theory (sociology) , algorithm , biology , control (management) , botany , computer security
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.