ON THE TARGET CLASSIFICATION THROUGH WAVELET-COMPRESSED SCATTERED ULTRAWIDE-BAND ELECTRIC FIELD DATA AND ROC ANALYSIS

This paper's aim is to classify cylindrical targets from their ultrawide-band radar returns. To calculate the radar returns, image technique formulation is used to obtain the Electric Field Integral Equations (EFIEs). Then, the EFIEs are solved numerically by Method of Moment (MoM). Because of wide frequency range of the ultrawide-band radar signal, the database to be used for target classification becomes very large. To deal with this problem and to provide robustness, wavelet transform is utilized. Application of wavelet transform significantly reduces the size of the database. The coefficients obtained by wavelet transform are used as the inputs of the artificial neural networks (ANNs). Then, the actual performances of the networks are investigated by Receiver Operating Characteristic (ROC) analysis.