Application of Ultra-Wide Band Radar for Sense-Through-Foliage Target Detection and Recognition

In this paper, we propose a new approach to detect and recognize the target obscured by foliage based on real data collected by an Ultra-wide band (UWB) radar sensor. The new proposed method is the combination of support vector machine (SVM) and memetic algorithm. SVM is a powerful tool for solving the recognition problem with small sampling, nonlinearity and high dimension. Memetic algorithm is applied to determine the optimal parameters for SVM with highest accuracy and generalization ability. Moreover, the feature vectors for target detection and recognition are obtained from target echo signal that processed by wavelet packet transform (WPT). The results of the experiments indicate that this proposed approach is an effective method for sense-through-foliage target detection and recognition, which has higher recognition accuracy than that of the artificial neural network and the SVM which has randomly extracted parameters.