综述视觉反无人机技术现状与挑战,助力复杂环境安全防护
Vision-Based Anti Unmanned Aerial Technology: Opportunities and Challenges
- 聚焦视觉与多传感器融合的反无人机检测追踪方法
- 梳理主流算法并整理公开数据集供研究复用
- 适合安全防护、边境巡逻等场景的研究者参考
随着无人机技术快速发展及其在军事侦察、环境监测和物流等领域的广泛应用,实现高效精准的反无人机跟踪已成为迫切需求。该技术在公共安全、边境巡逻、搜救及农业监测等复杂环境中尤为重要。当前主流反无人机技术以计算机视觉为核心,尤其依赖多传感器数据融合与先进检测追踪算法。本文首先梳理反无人机检测与跟踪技术的特性与现存挑战,继而系统调研并整理多个公开可用的数据集,提供可访问链接以支持研究工作。同时,分析近年提出的多种基于视觉及视觉融合的反无人机检测与追踪算法。最后,结合前述研究,展望未来发展方向,旨在为该领域进步提供有益参考。
原文摘要 · Abstract (English)
With the rapid advancement of UAV technology and its extensive application in various fields such as military reconnaissance, environmental monitoring, and logistics, achieving efficient and accurate Anti-UAV tracking has become essential. The importance of Anti-UAV tracking is increasingly prominent, especially in scenarios such as public safety, border patrol, search and rescue, and agricultural monitoring, where operations in complex environments can provide enhanced security. Current mainstream Anti-UAV tracking technologies are primarily centered around computer vision techniques, particularly those that integrate multi-sensor data fusion with advanced detection and tracking algorithms. This paper first reviews the characteristics and current challenges of Anti-UAV detection and tracking technologies. Next, it investigates and compiles several publicly available datasets, providing accessible links to support researchers in efficiently addressing related challenges. Furthermore, the paper analyzes the major vision-based and vision-fusion-based Anti-UAV detection and tracking algorithms proposed in recent years. Finally, based on the above research, this paper outlines future research directions, aiming to provide valuable insights for advancing the field.
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