Target identification in foliage environment using selected bispectra and Extreme Learning Machine
Minglei You, Ting Chen Jiang · 2013
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.