Device-free indoor localization using a distributed network of autonomous UWB sensor nodes

Snezhana Jovanoska, R. Zetik, R. Thomä, F. Govaers, K. Wild, W. Koch
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引用次数: 9

Abstract

In this paper we describe a method for localization of multiple persons using a distributed network of autonomous ultra-wideband sensor nodes. The persons do not carry any devices or tags to aid their detection, but are instead detected by using the time variations they impose on the measured channel impulse response between a transmitter and a receiver. The described method uses background subtraction and constant false alarm rate algorithms for person detection. Range tracking is incorporated for removal of clutter and false observations. The range information of the persons with respect to each sensor is fused using a maximum likelihood function. Here, we analyze the influences of range tracking on location estimation. In addition, two location estimation approaches are compared. The first approach fuses the available range information of the persons with respect to all sensors of the network. In the second approach locations are estimated by each sensor node and are later fused with the location estimates from the other sensors. The system implementation and selected methods for device-free person range estimation and sensor data fusion are verified in a realistic measurement scenario with two moving persons and through-wall operation of all sensors. The method can be used for near real-time localization and tracking of multiple moving persons.
使用自主超宽带传感器节点的分布式网络进行无设备室内定位
本文描述了一种利用自主超宽带传感器节点组成的分布式网络进行多人定位的方法。这些人不携带任何设备或标签来帮助他们的检测,而是通过使用他们施加在发射器和接收器之间测量的信道脉冲响应上的时间变化来检测。所描述的方法使用背景减法和恒定虚警率算法进行人员检测。加入了距离跟踪以消除杂波和虚假观测。利用最大似然函数将人相对于每个传感器的距离信息进行融合。在此,我们分析了距离跟踪对定位估计的影响。此外,对两种位置估计方法进行了比较。第一种方法是对网络中所有传感器的可用距离信息进行融合。在第二种方法中,位置由每个传感器节点估计,然后与来自其他传感器的位置估计融合。在两个移动人员和所有传感器穿墙运行的实际测量场景中,验证了系统实现和选择的无设备人员距离估计和传感器数据融合方法。该方法可用于近实时定位和多运动人的跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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