[论文解读] Nuzzer: A Large-Scale Device-Free Passive Localization System for Wireless Environments

Moustafa Seifeldin, Moustafa Youssef|ArXiv.org|Aug 6, 2009

Indoor and Outdoor Localization Technologies参考文献 20被引用 28

一句话总结

Nuzzer 提出了一种大规模、无需设备的被动定位系统，利用现有的无线网络通过接收信号强度（RSS）测量来估计人体位置。通过构建被动无线电地图，并应用结合空间与时间平均的贝叶斯推理，该系统仅使用两台笔记本电脑和三个接入点，在1500 m²的办公环境中实现了1.82米的中位定位误差，展示了在真实、多径丰富的室内环境中具有高精度与可扩展性的能力。

ABSTRACT

The widespread usage of wireless local area networks 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 a device is attached to tracked entities. Recently, device-free passive localization (DfP) has been proposed where the tracked entity is neither required to carry devices nor participate actively in the localization process. DfP systems are based on the fact that RF signals are affected by the presence of people and objects in the environment. The DfP concept enables a wide range of applications including intrusion detection and tracking, border protection, and smart buildings automation. Previous studies have focused on small areas with direct line of sight and/or controlled environments. In this paper, we present the design, implementation and analysis of Nuzzer, a large-scale device-free passive localization system for real environments. Without any additional hardware, it makes use of the already installed wireless data networks to monitor and process changes in the received signal strength (RSS) transmitted from access points at one or more monitoring points. We present probabilistic techniques for DfP localization and evaluate their performance in a typical office building, rich in multipath, with an area of 1500 square meters. Our results show that the Nuzzer system gives device-free location estimates with less than 2 meters median distance error using only two monitoring laptops and three access points. This indicates the suitability of Nuzzer to a large number of application domains.

研究动机与目标

• 设计并实现一种适用于真实室内环境的可扩展、高精度无设备被动定位系统。
• 实现在无需被跟踪对象携带设备或主动参与情况下的定位。
• 在典型办公楼等大规模、多径丰富的环境中有效运行。
• 利用现有的无线基础设施（接入点和监控笔记本电脑）而无需额外硬件。
• 仅使用标准无线设备实现高精度与无处不在的覆盖。

提出的方法

• 在离线阶段构建被动无线电地图，存储已知位置的RSS测量值。
• 使用贝叶斯推理，基于实时RSS向量与被动无线电地图估计最可能的位置。
• 应用空间与时间平均作为后处理技术以提升定位精度。
• 依赖标准接入点和监控笔记本电脑（如配备无线网卡的笔记本）收集RSS数据。
• 处理由人体存在引起的RSS变化，利用信号衰减与多径效应。
• 无需视 Line-of-Sight（LOS）条件，因此在存在墙体和反射材料的复杂室内环境中具有鲁棒性。

实验结果

研究问题

• RQ1 无设备被动定位系统是否能在具有显著多径效应的大规模真实室内环境中实现高精度？
• RQ2 结合空间与时间平均的贝叶斯推理在RSS-based定位中的性能，与确定性或随机估计方法相比如何？
• RQ3 现有无线基础设施（接入点与笔记本）在无需额外硬件的情况下，能在多大程度上实现精确的定位？
• RQ4 该系统如何在大型室内区域（如办公楼）中保持可扩展性与无处不在的覆盖？
• RQ5 环境动态变化（如移动物体、干扰）对定位精度有何影响，又该如何缓解？

主要发现

• Nuzzer 在1500 m²、多径效应显著的办公建筑中实现了1.82米的中位定位误差。
• 通过使用空间与时间平均后处理技术，系统将误差降低了38%。
• Nuzzer 的性能比确定性技术高出3.7倍，比随机估计器高出7.7倍。
• Nuzzer 仅使用两台监控笔记本电脑和三个接入点即成功运行，证明了其硬件开销极低。
• 系统无需视 Line-of-Sight 或特殊硬件即可保持高精度，适用于真实世界部署。
• 被动无线电地图的构建使系统在具有动态信号衰落与干扰的复杂室内环境中仍能实现鲁棒定位。