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Multitarget-Multisensor Management for Decentralized Sensor Networks

机译:分散式传感器网络的多目标多传感器管理

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In this paper, we consider the problem of sensor resource management in decentralized tracking systems. Due to the availability of cheap sensors, it is possible to use a large number of sensors and a few fusion centers (FCs) to monitor a large surveillance region. Even though a large number of sensors are available, due to frequency, power and other physical limitations, only a few of them can be active at any one time. The problem is then to select sensor subsets that should be used by each FC at each sampling time in order to optimize the tracking performance subject to their operational constraints. In a recent paper [14], we proposed an algorithm to handle the above issues for joint detection and tracking, without using simplistic clustering techniques that are standard in the literature. However, in that paper, a hierarchical architecture with feedback at every sampling time was considered, and the sensor management was performed only at a central fusion center (CFC). However, in general, it is not possible to communicate with the CFC at every sampling time, and in many cases there may not even be a CFC. Sometimes, communication between CFC and local fusion centers might fail as well. Therefore performing sensor management only at the CFC is not viable in most networks. In this paper, we consider an architecture in which there is no CFC, each FC communicates only with the neighboring FCs, and communications are restricted. In this case, each FC has to decide which sensors are to be used by itself at each measurement time step. We propose an efficient algorithm to handle the above problem in real time. Simulation results illustrating the performance of the proposed algorithm are also presented.
机译:在本文中,我们考虑了分散跟踪系统中传感器资源管理的问题。由于廉价传感器的可用性,有可能使用大量传感器和少数融合中心(FC)来监视大型监视区域。即使有大量传感器可用,但由于频率,功率和其他物理限制,在任何时候都只有少数几个传感器处于活动状态。然后的问题是选择每个FC在每个采样时间应使用的传感器子集,以便根据其操作约束来优化跟踪性能。在最近的一篇论文中[14],我们提出了一种用于解决上述问题的联合检测和跟踪算法,而无需使用文献中标准的简单聚类技术。但是,在该论文中,考虑了在每个采样时间均具有反馈的分层体系结构,并且仅在中央融合中心(CFC)进行传感器管理。但是,通常不可能在每个采样时间都与CFC通信,并且在许多情况下甚至可能没有CFC。有时,CFC与本地融合中心之间的通信也可能会失败。因此,在大多数网络中,仅在CFC上执行传感器管理是不可行的。在本文中,我们考虑一种没有CFC的体系结构,每个FC仅与相邻的FC通信,并且通信受到限制。在这种情况下,每个FC必须决定在每个测量时间步长将自己使用哪些传感器。我们提出一种有效的算法来实时处理上述问题。仿真结果也说明了所提出算法的性能。

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