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首页> 外文期刊>Mobile Computing, IEEE Transactions on >Nuzzer: A Large-Scale Device-Free Passive Localization System for Wireless Environments
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Nuzzer: A Large-Scale Device-Free Passive Localization System for Wireless Environments

机译：Nuzzer：用于无线环境的大型无设备被动定位系统

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摘要

The widespread usage of WLANs and mobile devices has fostered the interest in localization systems for wireless environments. The majority of research in the context of wireless-based localization systems has focused on device-based active localization, in which devices are attached to tracked entities. Recently, device-free passive localization (DfP) has been proposed where the tracked entity is neither required to carry devices nor to participate actively in the localization process. Previous studies have focused on small areas and/or controlled environments. In this paper, we present the design, implementation, and analysis of Nuzzer, a large-scale DfP localization system, which tracks entities in real environments, rich in multipath. We first present probabilistic techniques for DfP localization of a single entity and evaluate their performance both analytically and in typical office buildings. Our results show that Nuzzer gives location estimates with less than 2-meters median distance error. We then give an algorithm for estimating the number of entities in an area of interest and localizing them into coarse-grained zones to enhance the scalability of the system. This indicates the suitability of Nuzzer to a large number of application domains.
机译：WLAN和移动设备的广泛使用引起了人们对无线环境定位系统的兴趣。在基于无线的定位系统的背景下，大多数研究都集中在基于设备的主动定位上，其中设备被附加到被跟踪的实体上。近来，已经提出了无设备无源定位（DfP），其中被跟踪实体既不需要携带设备也不需要主动参与定位过程。先前的研究集中在小区域和/或受控环境上。在本文中，我们介绍了Nuzzer的设计，实现和分析，Nuzzer是一个大型DfP本地化系统，它可以跟踪真实环境中的实体，其中包含多路径。我们首先介绍用于单个实体的DfP本地化的概率技术，并通过分析和在典型办公大楼中评估其性能。我们的结果表明，Nuzzer给出的位置估计中值距离误差小于2米。然后，我们给出一种算法，用于估计感兴趣区域中实体的数量并将其定位到粗粒度区域以增强系统的可伸缩性。这表明Nuzzer适用于大量应用程序域。

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