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Optimal Receiver Placement for K-barrier Coverage in Passive Bistatic Radar Sensor Networks

机译:无源双孔雷达传感器网络中K屏障覆盖的最佳接收器放置

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The improvement of coverage quality in the construction of multiple-barrier coverage is a critical problem in a wireless sensor network. In this article, we investigate the K-barrier coverage construction problem in passive bistatic radar sensor networks. In contrast to traditional bistatic radar networks, the transmitters in a passive bistatic radar network are predeployed and noncooperative. To construct K barriers, we need to deploy receivers that couple with predeployed transmitters to build continuous barriers. In this work, we focus on the minimum number of receivers problem of constructing K-barrier coverage, where the minimum number of receivers is based on the predeployed transmitters. To handle this problem, we first investigate the optimal placement of receivers between adjacent transmitters for a sub-barrier formation and then determine the optimal placement of receivers for the one-barrier construction. For multiple-barrier coverage construction, we introduce a weighted transmitter graph (WTG) to describe the relation among different transmitters, where the weight in the graph is the minimum number of receivers needed for these two transmitters for a sub-barrier formation. Based on WTG, the minimum receivers problem changes to a problem of how to find K-disjoint paths with the minimum total weight in the graph. For large-scale networks, we also propose two efficient heuristic algorithms to solve the corresponding problem. Finally, we conduct extensive experiments to validate the correctness and the efficiency of the proposed algorithms.
机译:在多屏障覆盖的构造中的覆盖质量的提高是无线传感器网络中的一个关键问题。在本文中,我们研究了被动双磁雷达传感器网络中的K-Brilier覆盖施工问题。与传统的双弦雷达网络相比,被动双磁雷达网络中的发射器被预先部署和非合作。要构建K障碍,我们需要部署与预先部署的发射机加上的接收器来构建连续障碍。在这项工作中,我们专注于构建k阻隔覆盖的最小接收器问题,其中最小数量的接收器基于预制的发射机。为了处理这个问题,我们首先研究相邻发射器之间的接收器的最佳位置,用于子屏障形成,然后确定接收器的最佳放置用于单屏障结构。对于多屏障覆盖结构,我们引入加权发射器图(WTG)来描述不同发射机之间的关系,其中图中的重量是这两个发射机用于子屏障形成所需的最小接收器数。基于WTG,最小接收器问题更改了如何在图中找到具有最小总重量的K-Disjoint路径的问题。对于大型网络,我们还提出了两个有效的启发式算法来解决相应的问题。最后,我们进行了广泛的实验,以验证所提出的算法的正确性和效率。

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