Feature Extraction Method of Narrow-band Radar Airplane Signatures Based on Fractional Fourier Transform
DU Lan SHI Huiruo LI Linsen SUN Yongguang HU Jing
(National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China)
(Collaborative Innovation Center of Information Sensing and Understanding, Xidian University, Xi’an 710071, China)
This paper studies on the feature extraction methods for the classification of helicopter, propeller-driven aircraft, and turbojet using a conventional narrow-band radar system. In the modern battlefield, the helicopter, propeller aircraft and jet aircraft with different motor performances each bear an important task. But the classification performance of the traditional features for the three types of aircraft target classification is not good enough, so the Fractional Fourier Transform (FrFT) is introduced. Based on the existing feature extraction method, the fractional order features of three kinds of aircraft targets are extracted from the fractional domain after FrFT to extend feature domain. Then, the effective features are selected from all extracted features and the classification of the three categories via linear Relevance Vector Machine (RVM) is realized. The experiments demonstrate that the proposed fractional features can improve the classification performance in comparison with some existing features from the time-domain and Doppler-frequency domain.
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