无人机与鸟类识别的微多普勒特征深入分析

2020 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2020-01-01 DOI:10.1109/ICEIC49074.2020.9051232

Sanghong Park, Jooho Jung, Sangbin Cha, Soo-Bum Kim, SeWon Youn, Iksoo Eo, B. Koo

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引用次数: 3

摘要

本文结合实际飞行场景，对无人机和鸟类的微多普勒(MD)特征进行了各种特征的分类。利用旋转叶片和由板和椭球构成的扑翼进行分类的结果表明，MD带宽是最有效的特征。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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.

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2020 International Conference on Electronics, Information, and Communication (ICEIC)

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