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In-depth Analysis of the Micro-Doppler Features to Discriminate Drones and Birds

机译:深入分析微多普勒功能以区分无人机和鸟类

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摘要

This paper presents the classification result of various features obtained from the micro-Doppler(MD) signature of drones and birds considering the real flight scenarios. Classification results using the rotating blade and the flapping wing made of the plate and the ellipsoid demonstrate that the MD bandwidth is the most efficient feature.
机译:本文提出了从无人机和鸟类的微多普勒(MD)签名获得的各种特征的分类结果,其中考虑了真实的飞行场景。使用旋转叶片以及由板和椭球制成的襟翼进行分类的结果表明,MD带宽是最有效的功能。

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