使用监督机器学习识别无人机编队意图

Ahmad Traboulsi, M. Barbeau
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引用次数: 6

摘要

无人机正在成为国防应用、地理监视、包裹递送等领域的重要组成部分,其用途正在扩大。无人机活动检测与识别已成为一个重要的研究课题。一个更具挑战性的问题是识别一组无人机的意图。他们的意图可能并不明显,这可能在一些情况下造成安全威胁。识别一组无人机的目标计划是本文的研究课题。我们专注于识别一组无人机试图达到的编队。我们使用softmax回归预测了从一个地层到另一个地层过渡阶段的地层。我们测试了几个特征向量设计,并给出了我们的结果
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recognition of Drone Formation Intentions Using Supervised Machine Learning
Drones are becoming a major element in defense applications, geographic surveillance, delivery of packages and their uses are expanding. Drone activity detection and identification have become an important research subject. An even more challenging problem is recognizing the intentions of a group of drones. Their intention may not be obvious, which might impose a security threat in several instances. Recognizing the targeted plan of a group of drones is the subject of study in this paper. We focus on identifying the formation a group of drones is trying to achieve. We predict the formation during the transition phase from one formation to another using softmax regression. We test several feature vector designs and present our results
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