首页> 外文OA文献 >Determining a cost-effective mix of UAV-USV-manned platforms to achieve a desired level of surveillance in a congested strait
【2h】

Determining a cost-effective mix of UAV-USV-manned platforms to achieve a desired level of surveillance in a congested strait

机译:确定在无人机拥挤的海峡中实现高性价比的无人机-无人驾驶无人机平台,以实现所需的监视水平

摘要

This thesis develops concepts of operations (CONOPS) and analytical models to determine the surveillance assets for a congested strait. Two maritime security threats (Reds) are a hijacked large ship carrying dangerous cargo or a SB manned by terrorists attempting to cause damage to other vessels or the port. The Red SB can either conduct a direct attack or a sneak attack by hiding among other neutral SBs. The defense force consists of shore-based sensors, unmanned aerial vehicles (UAVs), unmanned surface vehicles (USVs), and patrol craft (PC). The shore-based radar and the UAVs classify unidentified vessels as suspicious or not suspicious and suspicious SB must be inspected by a USV or PC. Analytical models are introduced to analyze requirements for numbers of surveillance assets and to assess the effectiveness of the CONOPS to achieve a desired probability of detecting and intercepting the threat. They incorporate both differential equations and probabilistic arguments. Results indicate that if the UAVs generate many false positives then the USVs and PCs have a higher workload which decreases the probability of detecting a threat. USVs and PCs should give a high priority to inspecting suspicious SBs rather than identifying unsuspicious SBs to achieve a higher probability of detecting a threat.
机译:本文提出了作战概念(CONOPS)和分析模型,以确定拥挤海峡的监视资产。两个海上安全威胁(红色)是劫持的载有危险货物的大船,或者是恐怖分子操纵的SB,企图破坏其他船只或港口。红色SB可以躲在其他中立SB中进行直接攻击或偷袭。国防军包括岸基传感器,无人机(UAV),无人机(USV)和巡逻艇(PC)。岸基雷达和无人机将未识别的船只分类为可疑或不可疑,可疑SB必须由USV或PC检查。引入了分析模型,以分析监视资产数量的需求,并评估CONOPS的有效性,以达到检测和拦截威胁所需的概率。它们同时包含了微分方程和概率论证。结果表明,如果无人机产生许多误报,则USV和PC的工作量就会增加,这会降低检测到威胁的可能性。 USV和PC应高度重视检查可疑SB,而不是识别不可疑SB以提高检测威胁的可能性。

著录项

  • 作者

    Chng Kim Chuan;

  • 作者单位
  • 年度 2007
  • 总页数
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 入库时间 2022-08-20 20:55:55

相似文献

  • 外文文献
  • 中文文献
  • 专利

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