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On Topology of Sensor Networks Deployed for Multitarget Tracking

机译：论用于多目标跟踪的传感器网络拓扑

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摘要

In this paper, we study topologies of sensor networks deployed for tracking multiple targets. Tracking multiple moving targets is a challenging problem. Most of the previously proposed tracking algorithms simplify the problem by assuming access to the signal from an individual target for tracking. Recently, tracking algorithms based on blind source separation (BSS), a statistical signal-processing technique widely used to recover individual signals from mixtures of signals, have been proposed. BSS-based tracking algorithms are proven to be effective in tracking multiple indistinguishable targets. The topology of a wireless sensor network deployed for tracking with BSS-based algorithms is critical to tracking performance because the topology affects separation performance, and the topology determines accuracy and precision of estimation on the paths taken by targets. We propose cluster topologies for BSS-based tracking algorithms. Guidelines on parameter selection for proposed topologies are given in this paper. We evaluate the proposed cluster topologies with extensive experiments. Our experiments show that the proposed topologies can significantly improve both the accuracy and the precision of BSS-based tracking algorithms.
机译：在本文中，我们研究了部署用于跟踪多个目标的传感器网络的拓扑。跟踪多个移动目标是一个具有挑战性的问题。大多数先前提出的跟踪算法通过假设访问来自单个目标的信号进行跟踪来简化此问题。近来，已经提出了基于盲源分离（BSS）的跟踪算法，它是一种广泛用于从信号混合中恢复单个信号的统计信号处理技术。事实证明，基于BSS的跟踪算法可有效跟踪多个无法区分的目标。部署用于使用基于BSS的算法进行跟踪的无线传感器网络的拓扑结构对跟踪性能至关重要，因为该拓扑结构会影响分离性能，并且拓扑结构会确定目标所采用路径的估计精度和精确度。我们为基于BSS的跟踪算法提出了集群拓扑。本文给出了建议拓扑的参数选择指南。我们通过广泛的实验评估提出的集群拓扑。我们的实验表明，提出的拓扑可以显着提高基于BSS的跟踪算法的准确性和准确性。

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