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논문 기본 정보

자료유형
학술저널
저자정보
In-Ha Kim (Hannam University) In-Sik Choi (Hannam University) Dae-Young Chae (Agency for Defense Development)
저널정보
한국전자파학회JEES Journal of Electromagnetic Engineering And Science Journal of Electromagnetic Engineering And Science Vol.18 No.3
발행연도
2018.7
수록면
206 - 211 (6page)

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초록· 키워드

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In this paper, we proposed a two-level feature vector fusion technique to improve the performance of target classification. The proposed method combines feature vectors of the early-time region and late-time region in the first-level fusion. In the second-level fusion, we combine the monostatic and bistatic features obtained in the first level. The radar cross section (RCS) of the 3D full-scale model is obtained using the electromagnetic analysis tool FEKO, and then, the feature vector of the target is extracted from it. The feature vector based on the waveform structure is used as the feature vector of the early-time region, while the resonance frequency extracted using the evolutionary programming-based CLEAN algorithm is used as the feature vector of the late-time region. The study results show that the two-level fusion method is better than the one-level fusion method.

목차

Abstract
I. INTRODUCTION
II. FEATURE VECTORS IN THE EARLY- AND LATE-TIME REGIONS
III. FEATURE VECTOR FUSION IN RADAR STRUCTURE
IV. TWO-LEVEL FEATURE FUSION METHOD
V. SIMULATION AND RESULTS
VI. CONCLUSION
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