Target detection and classification by uwb communication signal based on third-order cumulants

We have taken an experimental study about a novel method of the feasibility of ultra-wideband (UWB) communication system to concealed obstacles detection and classification. The recognition of target can be achieved by received UWB-IR signals from the UWB communication system which is different from traditional method using UWB radar echoes. In this paper, we propose a third-order statistic method to extract features that are representative of the target types from the received signals. Then, support vector machine (SVM) is used to realize the obstacle identification. The detection performance is compared with that of feature extraction method based on statistical characteristics of received signal (Ru Ying et al., Globecom Workshops (GC Wkshps), 2012 IEEE;1389-1393, 2012; Junqin He et al., Globecom Workshops (GC Wkshps), 2012 IEEE, 1460-1463, 2012). According to the experiment based on real data collected by the received signals of UWB communication, the results indicate that the detection method based on third-order cumulant shows better noise immunity than that based on statistical characteristics.