无人机的光学与光谱检测与识别方法

A. Morozov, A. L. Nazolin, I. Fufurin
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摘要

本文研究了用光学和光谱光学方法识别无人机对有生命和无生命物体的检测和识别及其载荷的问题。最先进的分析表明,当使用雷达方法检测小型无人机时,距离为250-700米存在死区,在这种情况下,使用光学方法检测无人机非常重要。考虑了光学方案在1 ~ 2 km远距离探测无人机的应用可能性和改进。定位是通过使用红外摄像机和热成像仪以及激光测距仪(LIDAR)的物体的固有红外(IR)辐射来完成的。本文给出了利用faster - cnn、YOLO和SSD网络模型,利用图论和神经网络方法对视频图像中的目标进行动态检测和识别的成功实例,其中包括接收到的一帧图像。已经研究了使用可用的光谱光学方法来分析可用于无人机涂层材料远程识别的材料的化学成分的可能性,以及用于检测其表面微量物质的可能性。介绍了紫外发光光谱学、拉曼光谱、基于可调谐紫外激光器的微分吸收光谱、光谱成像方法(超/多光谱图像)、红外可调谐量子级联激光器(QCL)的漫反射激光光谱学的优缺点。为了评估探测和识别无人机的潜在限制距离,以及通过光学和光谱光学方法识别物体的化学成分,所描述的实验装置(混合激光雷达无人机识别综合体)预计将是有用的。介绍了实验装置的结构和性能。这些研究旨在通过光学定位和光谱方法对无人机参数和不同类群的无人机进行远程检测、识别、跟踪和确定,以及在移动野生动物背景下的各种环境下对无人机进行自动光学识别的科学基础。提出的问题解决方案是将光学定位与光谱分析方法、统计学理论方法、图学方法、深度学习方法、神经网络方法和自动控制方法相结合,是一项跨学科的基础性科学任务。
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Optical and Spectral Methods for Detection and Recognition of Unmanned Aerial Vehicles
The paper considers a problem of detection and identification of unmanned aerial vehicles (UAVs) against the animate and inanimate objects and identification of their load by optical and spectral optical methods. The state-of-the-art analysis has shown that, when using the radar methods to detect small UAVs, there is a dead zone for distances of 250-700 m, and in this case it is important to use optical methods for detecting UAVs.The application possibilities and improvements of the optical scheme for detecting UAVs at long distances of about 1-2 km are considered. Location is performed by intrinsic infrared (IR) radiation of an object using the IR cameras and thermal imagers, as well as using a laser rangefinder (LIDAR). The paper gives examples of successful dynamic detection and recognition of objects from video images by methods of graph theory and neural networks using the network FasterR-CNN, YOLO and SSD models, including one frame received.The possibility for using the available spectral optical methods to analyze the chemical composition of materials that can be employed for remote identification of UAV coating materials, as well as for detecting trace amounts of matter on its surface has been studied. The advantages and disadvantages of the luminescent spectroscopy with UV illumination, Raman spectroscopy, differential absorption spectroscopy based on a tunable UV laser, spectral imaging methods (hyper / multispectral images), diffuse reflectance laser spectroscopy using infrared tunable quantum cascade lasers (QCL) have been shown.To assess the potential limiting distances for detecting and identifying UAVs, as well as identifying the chemical composition of an object by optical and spectral optical methods, a described experimental setup (a hybrid lidar UAV identification complex) is expected to be useful. The experimental setup structure and its performances are described. Such studies are aimed at development of scientific basics for remote detection, identification, tracking, and determination of UAV parameters and UAV belonging to different groups by optical location and spectroscopy methods, as well as for automatic optical UAV recognition in various environments against the background of moving wildlife. The proposed problem solution is to combine the optical location and spectral analysis methods, methods of the theory of statistics, graphs, deep learning, neural networks and automatic control methods, which is an interdisciplinary fundamental scientific task.
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