无人机动态雷达组网：一种联合导航跟踪方法
Dynamic Radar Network of UAVs: A Joint Navigation and Tracking Approach
摘要：
如今，有越来越多的研究兴趣的可能性，丰富的小型飞行机器人与自主传感和在线导航能力。这将使大量的应用程序，从远程监控到物流，智能城市和危险环境中的紧急援助。在这种背景下，一个新出现的问题是跟踪隐藏在建筑物后面或隐藏在大型无人机网络中的未经授权的小型无人机（UAV）。与目前主要基于静态和地面雷达的解决方案相比，本文提出了无人机动态雷达网络的思想，用于实时和高精度跟踪恶意目标。为此，我们描述了一种解决方案，用于实时导航的无人机跟踪一个动态的目标，使用异构感测信息。这些信息由UAV通过多跳与它们的邻居共享，允许通过在每个代理处运行的本地贝叶斯估计器来跟踪目标。由于并非所有的路径都是平等的信息收集点的观点，无人机规划自己的轨迹，通过最小化后验协方差矩阵的目标状态下无人机运动学和防碰撞的约束。我们的研究结果表明，与固定配置相比，动态雷达网络如何获得更好的定位结果，以及机载传感器技术如何影响跟踪具有不同雷达截面的目标的精度，特别是在非视线（NLOS）情况下。
英文摘要：
Nowadays there is a growing research interest on the possibility of enriching small flying robots with autonomous sensing and online navigation capabilities. This will enable a large number of applications spanning from remote surveillance to logistics, smarter cities and emergency aid in hazardous environments. In this context, an emerging problem is to track unauthorized small unmanned aerial vehicles (UAVs) hiding behind buildings or concealing in large UAV networks. In contrast with current solutions mainly based on static and on-ground radars, this paper proposes the idea of a dynamic radar network of UAVs for real-time and high-accuracy tracking of malicious targets. To this end, we describe a solution for real-time navigation of UAVs to track a dynamic target using heterogeneously sensed information. Such information is shared by the UAVs with their neighbors via multi-hops, allowing tracking the target by a local Bayesian estimator running at each agent. Since not all the paths are equal in terms of information gathering point-of-view, the UAVs plan their own trajectory by minimizing the posterior covariance matrix of the target state under UAV kinematic and anti-collision constraints. Our results show how a dynamic network of radars attains better localization results compared to a fixed configuration and how the on-board sensor technology impacts the accuracy in tracking a target with different radar cross sections, especially in non line-of-sight (NLOS) situations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
