Based On Time-frequency Analysis Of Radar Target Recognition Technology

In this thesis, focused on the targets in air with micro-movement, radar target recognition based on high resolution time-frequency analysis is studied. The main research work includes:1. GRECO software -a high frequency electromagnetic calculation software, is improved with target movement trajectory processing module and radar emission waveform selection module. Three targets with simple structure, such as cone, sphere and cone, cylinder and cone, are modeled and their dynamic RCS echo signals in different movement are estimated.2. Three time-frequency analysis methods, including the Wigner-Ville transform, short time Fourier transform (STFT) and wavelet transform, are introduced. Dynamic RCS echo signals of movement targets are processed by using short time Fourier transform, and high-resolution time-frequency distribution images are achieved.3. A new radar target recognition method based on time-frequency distribution images is proposed. Pixel scan technique is adopted to extract the feature vector, and the nearest neighbor classifier is used for classification decision. Compared with the target recognition method based on singular value decomposition, the correction probability for recognition of the proposed method is higher. Simulation results verify the correctness and the effectiveness of the proposed method.