In recent years, the application of UAV drones in environmental monitoring, precision agriculture, and forestry surveys has grown exponentially. These
Our research systematically investigates the application of China UAV inspection technology within the power supply sector. From the dual perspectives
In my research I investigate how the individual migration behaviour of a single UAV drone can reshape the collective fate
The rapid advancement of military UAV (Unmanned Aerial Vehicle) technology has fundamentally transformed the landscape of modern warfare and military
The efficacy of modern multi-drone operations hinges not merely on the aggregate capability of individual platforms but on the sophisticated,
In this work, we present a comprehensive study on cooperative formation control algorithms and collision avoidance strategies for fixed-wing drones.
In modern robotics and autonomous systems, quadrotor drones have emerged as a pivotal technology due to their agility, vertical take-off
In recent years, the adoption of agricultural drones has revolutionized pest and disease control in crop management. As a researcher
The proliferation of Unmanned Aerial Vehicles (UAVs), ranging from sophisticated military platforms to commercially available, modified drones, represents one of
As a researcher and practitioner in the field of firefighting and rescue operations, I have witnessed the transformative impact of
With the rapid advancement of surveying and mapping technology, the industry is shifting from traditional coarse-grained operations to high-precision, efficient,
In the rapidly evolving landscape of emergency communication, the need for robust, flexible, and wide-area coverage solutions has become paramount.
In the era of rapid development of the Internet of Things and fifth-generation mobile communication technology, the application scenarios of
In recent years, the proliferation of “low, slow, and small” unmanned aerial vehicles (UAVs) has posed significant security challenges, leading
In modern agriculture, the mid to late growth stages of wheat are critical for yield formation, yet they are also
As a researcher focused on naval defense systems, I observe that the maritime battlespace is undergoing a profound transformation. For
In recent years, the use of unmanned aerial vehicles (UAVs) has revolutionized various monitoring applications, from agricultural surveillance to environmental
The coordinated operation of drone swarms has become a pivotal research area, overcoming the limitations of single-agent systems in terms
In recent years, UAV drones have become increasingly important in public security, disaster monitoring, urban governance, traffic surveillance, and emergency
In the context of hydrographic comprehensive remediation projects, the rapid advancement of lidar and communication technologies has significantly promoted the
近年来，低空无人机的快速发展在军事和民用领域带来了广泛的应用前景，但同时也引发了日益严峻的安全隐患。针对无人机目标实现高效识别与持续跟踪，是实施各类防御与反制工作的基础前提。在无人机检测与跟踪任务中，由于目标体积较小并受到拍摄距离、视角变化等因素的影响，其目标通常存在显著的尺度变化，同时易受复杂背景干扰，甚至出现目标暂时消失的现象。针对以上问题，本文围绕无人机的检测与跟踪关键技术展开深入研究，提出了一系列改进算法，并在嵌入式平台上完成了工程验证。 1 引言 1.1 研究背景与意义 随着低空空域管理政策的逐步放宽以及飞行控制技术的持续成熟，无人机凭借其低成本、高机动性以及卓越的成像能力，在物流运输、测绘与地理信息、农林植保、巡检、应急救援以及消费娱乐等多个行业实现了规模化应用。在军事应用领域，无人机已成为现代战争中的重要作战力量，能够执行侦察巡逻、电子干扰、精确打击等多种任务。然而，无人机的广泛使用也带来了严峻的安全问题。军事设施、民航机场、重要集会场所等关键区域频繁遭受无人机的非法入侵，对国家安全和公共安全构成了严重威胁。 反无人机系统的效能在很大程度上依赖于其目标检测能力。无人机具有体积小、散热能力差、雷达反射截面有限、飞行高度较低且常用复合材料制造等特点，这些特性使得传统的雷达、射频或声传感器等探测设备的检测效能显著降低。在此背景下，利用光电信息技术探测无人机，特别是结合人工智能算法的视觉检测方法，展现出强大的应用潜力。此类方法可精确提取目标的位置、尺寸以及外观特征，已成为未来无人机探测技术发展的重要方向。深入研究无人机视觉检测技术可以与雷达探测、无源定位等多种技术协同工作，有效提高低空目标的识别率与跟踪精度，为后续干扰拦截操作提供支持。 1.2 国内外研究现状 在反无人机技术领域，现有的反无人机系统主要可以分为干扰阻断类、摧毁捕获类和探测跟踪类。干扰阻断类系统通过无线电干扰、虚假信号注入、通信链路阻断以及导航欺骗等手段削弱或直接中断无人机的控制能力；摧毁捕获类系统则通过常规火力、导弹以及激光武器等手段实现物理摧毁；探测跟踪类系统集成雷达、红外热成像、声学传感器和通信模块等多种先进设备，能够在动态战场中实现远距离、高精度的探测与跟踪。尽管多种反无人机系统在战场对抗中占据主导地位，但在民用领域的应用却面临系统造价昂贵、复杂环境下性能衰减以及有效作用距离不足等挑战。 在目标检测算法领域，传统方法主要依赖人工特征提取与分类器的结合，如VJ检测器、HOG检测器以及DPM等方法。这类方法在简单场景下能够取得一定效果，但面对复杂背景或多尺度目标时往往存在较大局限性。随着深度学习技术的快速发展，基于卷积神经网络的目标检测算法迅速涌现。两阶段检测算法以R-CNN、Fast R-CNN和Faster R-CNN为代表，通过候选区域提取和精细分类两个阶段实现高精度检测；单阶段检测算法以YOLO系列和SSD为代表，直接在特征图上进行回归，实现了端到端的实时检测。YOLOv8作为YOLO系列中的代表性算法，通过对网络结构的持续优化，在检测精度与速度之间取得了良好的平衡，成为无人机检测任务中广泛使用的基准模型。 在目标跟踪算法领域，传统的跟踪方法主要分为生成式方法和判别式方法。生成式方法通过构建目标的外观模型来实现跟踪，如粒子滤波、均值漂移等；判别式方法通过训练二元分类器来分离前景与背景，如相关滤波方法和基于深度学习的跟踪方法。基于检测的跟踪框架（tracking-by-detection）近年来获得了极大关注，其中ByteTrack算法通过高效利用低置信度检测框，实现了高质量的轨迹关联，但其性能仍受限于检测器的精度和卡尔曼滤波的预测能力。 2 目标检测与跟踪相关理论 2.1 深度学习相关理论基础 人工神经网络是深度学习的基础架构，其基本处理单元为感知器。在感知器结构中，\(x_i\)表示输入的特征向量，\(w_i\)对应各特征的权重参数，\(b\)为偏移量。当加权特征与偏移量相加后，通过非线性激活函数\(f\)进行转换，最终输出结果\(y\)的数学表达式为： $$
The advent of unmanned aerial vehicle (UAV) technology has catalyzed innovations across numerous fields, with one of the most visually
The sustainable management and protection of forest resources represent a critical challenge in balancing ecological integrity with socio-economic development. This
The scale and complexity of modern industrial park construction projects have increased dramatically, making slope stability a paramount factor for
In the rapidly evolving landscape of e-commerce and low-altitude economies, traditional last-mile delivery models are increasingly inadequate. The integration of
In recent years, quadrotor drones have gained significant attention due to their versatility in applications such as logistics, surveillance, and
In order to enhance the coverage capability of emergency communication using fixed-wing UAVs, I have developed a novel fixed-wing UAV
Unmanned aerial vehicle technology has matured rapidly over the past decade, and the UAV drone has evolved from a specialized
In recent years, the coordination control of multi-drone systems has garnered significant attention due to its robustness, flexibility, scalability, and
In the realm of modern precision agriculture, the utilization of low-altitude economic machinery, particularly unmanned aerial vehicles (UAVs), has revolutionized
