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Triangulation Based Multi Target Tracking with Mobile Sensor Networks

机译:移动传感器网络的基于三角剖分的多目标跟踪

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We study the problem of designing motion-planning and sensor assignment strategies for tracking multiple targets with a mobile sensor network. We focus on triangulation based tracking where two sensors merge their measurements in order to estimate the position of a target. We present an iterative and distributed algorithm for the tracking problem. An iteration starts with an initialization phase where targets are assigned to sensor pairs. Afterwards, assigned sensors relocate to improve their estimates. We refer to the problem of computing new locations for sensors (for given target assignments) as one-step tracking. After observing that one-step tracking is computationally hard, we show how it can be formulated as an energy-minimization problem. This allows us to adapt well-studied distributed algorithms for energy minimization. We present simulations to compare the performance of two such algorithms and conclude the paper with a description of the full tracking strategy. The utility of the presented strategy is demonstrated with simulations and experiments on a sensor network platform
机译:我们研究了设计运动计划和传感器分配策略以使用移动传感器网络跟踪多个目标的问题。我们专注于基于三角测量的跟踪,其中两个传感器合并其测量值以估计目标的位置。我们提出了一种跟踪问题的迭代和分布式算法。迭代从初始化阶段开始,在该阶段将目标分配给传感器对。此后,分配的传感器重新定位以改善其估计值。我们将计算传感器(针对给定目标分配)的新位置的问题称为一步跟踪。在观察到单步跟踪在计算上很困难之后,我们展示了如何将其公式化为能量最小化问题。这使我们能够对经过深入研究的分布式算法进行调整,以实现能耗最小化。我们提出了仿真,以比较两种此类算法的性能,并以完整跟踪策略的描述作为结论。在传感器网络平台上的仿真和实验证明了所提出策略的实用性

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