首页> 外文期刊>Computer networks >Performance modeling and analysis of a UAV path planning and target detection in a UAV-based wireless sensor network
【24h】

Performance modeling and analysis of a UAV path planning and target detection in a UAV-based wireless sensor network

机译:基于无人机的无线传感器网络中无人机路径规划和目标检测的性能建模和分析

获取原文
获取原文并翻译 | 示例
       

摘要

A wireless sensor network (WSN) is usually deployed in a field-of-interest (Fol) for detecting or monitoring special events. Traditionally, the WSN requires intensive deployment in which extra sensor nodes are deployed to achieve the required coverage level. In recent years, the UAV has been widely adopted in both military and civilian applications, depending on the development of unmanned aerial vehicle (UAV) techniques. Compared with traditional mobile sensor nodes, the UAV has much faster moving speed, longer deployment range and a relatively longer operating time. Consequently, the UAV can be considered as a perfect carrier for the existing sensing equipment, and can be used to form a UAV-based WSN (UWSN). Naturally, in order to determine the efficiency of a UWSN, we should investigate further the probability of detecting a target in the Fol if a UAV randomly scanned the Fol n times. Towards this end, we propose in this article to analyze theoretically the target detection problem in a UWSN by considering both static and mobile targets, respectively. We further analyzed the UAV Path Planning problem, and derived the optimal moving scenario for the UAV to detect a target. The experimental results further verified our theoretical results. (C) 2018 Elsevier B.V. All rights reserved.
机译:无线传感器网络(WSN)通常部署在关注领域(Fol)中,用于检测或监视特殊事件。传统上,WSN需要密集部署,其中部署额外的传感器节点以达到所需的覆盖级别。近年来,根据无人机技术的发展,无人机已广泛应用于军事和民用领域。与传统的移动传感器节点相比,无人机具有更快的移动速度,更长的部署范围和相对更长的运行时间。因此,无人机可以被认为是现有传感设备的理想载体,并且可以用于形成基于无人机的WSN(UWSN)。自然地,为了确定UWSN的效率,如果UAV随机扫描Fol N次,我们应该进一步研究在Fol中检测到目标的可能性。为此,我们在本文中建议从理论上分析UWSN中的目标检测问题,方法是分别考虑静态目标和移动目标。我们进一步分析了无人机路径规划问题,并得出了无人机探测目标的最佳运动场景。实验结果进一步验证了我们的理论结果。 (C)2018 Elsevier B.V.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号