Enhancing Resolution and Fault Tolerance of Barrier Coverage with Unmanned Aerial Vehicles

IF 1.3 4区 工程技术 Q2 ENGINEERING, AEROSPACE Journal of Aerospace Information Systems Pub Date : 2024-05-06 DOI:10.2514/1.i011298
Amit Kumar, Debasish Ghose
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Abstract

Securing the borders of a protected region using sensor network deployment is termed “barrier coverage.” Unmanned aerial vehicles (UAVs) with cameras pointed downward can serve as mobile sensors to achieve barrier coverage of a protected region. The resolution of the camera, in addition to the extent of coverage, is a crucial parameter used to evaluate the quality of barrier coverage of a region. This paper presents a cost function that measures the resolution of a barrier coverage network, which can be used to improve the quality of an already established barrier-covered network. An optimization problem is proposed to find the barrier coverage while adhering to an overlapping constraint for UAVs that are placed arbitrarily in the belt. The approach is also demonstrated to be applicable for borders of any shape by utilizing multiple rectangular belts in combination. Furthermore, a fault tolerance model is proposed to ensure continuous barrier coverage even in the presence of faulty UAVs. This model utilizes nearby functional UAVs to compensate for any gaps and preserve the overlap constraint. Specifically, the model identifies neighboring functional UAVs for each faulty UAV and uses them to maintain barrier coverage.

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利用无人飞行器提高障碍物覆盖的分辨率和容错能力
利用传感器网络部署确保受保护区域边界的安全被称为 "屏障覆盖"。装有摄像头的无人飞行器(UAV)可作为移动传感器,实现对受保护区域的障碍物覆盖。除了覆盖范围之外,摄像机的分辨率也是用于评估区域障碍物覆盖质量的关键参数。本文提出了一种衡量障碍物覆盖网络分辨率的成本函数,可用于提高已建立的障碍物覆盖网络的质量。本文提出了一个优化问题,以找到障碍物覆盖范围,同时为任意放置在带状区域的无人机遵守重叠约束。该方法还证明可通过组合使用多个矩形带,适用于任何形状的边界。此外,还提出了一种容错模型,以确保即使在无人飞行器出现故障的情况下也能持续覆盖障碍物。该模型利用邻近的功能性无人飞行器来弥补任何缺口,并保持重叠约束。具体来说,该模型为每个故障无人机识别邻近的功能无人机,并利用它们来保持障碍物覆盖范围。
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来源期刊
CiteScore
3.70
自引率
13.30%
发文量
58
审稿时长
>12 weeks
期刊介绍: This Journal is devoted to the dissemination of original archival research papers describing new theoretical developments, novel applications, and case studies regarding advances in aerospace computing, information, and networks and communication systems that address aerospace-specific issues. Issues related to signal processing, electromagnetics, antenna theory, and the basic networking hardware transmission technologies of a network are not within the scope of this journal. Topics include aerospace systems and software engineering; verification and validation of embedded systems; the field known as ‘big data,’ data analytics, machine learning, and knowledge management for aerospace systems; human-automation interaction and systems health management for aerospace systems. Applications of autonomous systems, systems engineering principles, and safety and mission assurance are of particular interest. The Journal also features Technical Notes that discuss particular technical innovations or applications in the topics described above. Papers are also sought that rigorously review the results of recent research developments. In addition to original research papers and reviews, the journal publishes articles that review books, conferences, social media, and new educational modes applicable to the scope of the Journal.
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