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Detection and Classification of Multirotor Drones in Radar Sensor Networks: A Review

机译:雷达传感器网络中多电流无人机的检测和分类:综述

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摘要

Thanks to recent technological advances, a new generation of low-cost, small, unmanned aerial vehicles (UAVs) is available. Small UAVs, often called drones, are enabling unprecedented applications but, at the same time, new threats are arising linked to their possible misuse (e.g., drug smuggling, terrorist attacks, espionage). In this paper, the main challenges related to the problem of drone identification are discussed, which include detection, possible verification, and classification. An overview of the most relevant technologies is provided, which in modern surveillance systems are composed into a network of spatially-distributed sensors to ensure full coverage of the monitored area. More specifically, the main focus is on the frequency modulated continuous wave (FMCW) radar sensor, which is a key technology also due to its low cost and capability to work at relatively long distances, as well as strong robustness to illumination and weather conditions. This paper provides a review of the existing literature on the most promising approaches adopted in the different phases of the identification process, i.e., detection of the possible presence of drones, target verification, and classification.
机译:由于最近的技术进步,新一代低成本,小型的空中车辆(无人机)可用。通常称为无人机的小无人机,正在实现前所未有的申请,但同时产生新的威胁与他们可能的误用(例如,毒品走私,恐怖主义攻击,间谍)相关联。在本文中,讨论了与无人机识别问题有关的主要挑战,包括检测,可能的验证和分类。提供了最相关技术的概述,其中在现代监控系统中被组成为空间分布式传感器网络,以确保全面覆盖受监控区域。更具体地,主焦点在频率调制的连续波(FMCW)雷达传感器上,这也是一种关键技术,也是由于其在相对长的距离上工作的低成本和能力,以及对照明和天气条件的强大鲁棒性。本文对现有文献进行了综述,以识别过程的不同阶段采用的最有前途的方法,即检测可能存在无人机,目标验证和分类。

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