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An Effective and Robust Decentralized Target Tracking Scheme in Wireless Camera Sensor Networks

机译:无线摄像头传感器网络中有效且鲁棒的分散目标跟踪方案

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摘要

In this paper, we propose an effective and robust decentralized tracking scheme based on the square root cubature information filter (SRCIF) to balance the energy consumption and tracking accuracy in wireless camera sensor networks (WCNs). More specifically, regarding the characteristics and constraints of camera nodes in WCNs, some special mechanisms are put forward and integrated in this tracking scheme. First, a decentralized tracking approach is adopted so that the tracking can be implemented energy-efficiently and steadily. Subsequently, task cluster nodes are dynamically selected by adopting a greedy on-line decision approach based on the defined contribution decision (CD) considering the limited energy of camera nodes. Additionally, we design an efficient cluster head (CH) selection mechanism that casts such selection problem as an optimization problem based on the remaining energy and distance-to-target. Finally, we also perform analysis on the target detection probability when selecting the task cluster nodes and their CH, owing to the directional sensing and observation limitations in field of view (FOV) of camera nodes in WCNs. From simulation results, the proposed tracking scheme shows an obvious improvement in balancing the energy consumption and tracking accuracy over the existing methods.
机译:在本文中,我们提出了一种基于平方根孵化信息过滤器(SRCIF)的有效而强大的分散式跟踪方案,以平衡无线摄像机传感器网络(WCN)的能耗和跟踪精度。更具体地说,针对WCN中摄像机节点的特性和约束,提出了一些特殊的机制并将其集成到此跟踪方案中。首先,采用分散式跟踪方法,以便可以高效,稳定地进行跟踪。随后,考虑摄像机节点的有限能量,通过基于定义的贡献决策(CD)采用贪婪的在线决策方法,动态选择任务集群节点。此外,我们设计了一种有效的簇头(CH)选择机制,该机制根据剩余能量和到目标的距离将选择问题转换为优化问题。最后,由于WCN中摄像机节点的视场(FOV)中的方向感测和观察限制,我们在选择任务集群节点及其CH时还对目标检测概率进行了分析。从仿真结果看,提出的跟踪方案与现有方法相比,在能耗和跟踪精度之间取得了明显的提高。

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