Redundancy reduction for indoor device-free localization

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• 作者：Jinjun Liu ; Ning An ; Md. Tanbir Hassan ; Min Peng…
• 关键词：Indoor passive localization ; Redundancy reduction ; Node optimization ; Node reduction ; Reducing the amount of data
• 刊名：Personal and Ubiquitous Computing
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：21
• 期：1
• 页码：5-15
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：User Interfaces and Human Computer Interaction; Computer Science, general; Personal Computing; Mobile Computing;
• 出版者：Springer London
• ISSN：1617-4917
• 卷排序：21

文摘

To improve localization accuracy, device-free passive localization studies usually deploy a number of sensor nodes in indoor environments, which causes redundant features and produces large data volumes and high deployment costs. This paper proposes the concept of a two-level redundancy and formulates the node reduction problem as a redundancy control problem. With the goal of using fewer nodes while maintaining high localization accuracy, a method is proposed to control the two-level redundancy efficiently and reduce the number of nodes greatly. Experiments are performed in two completely different environments. The proposed method is able to maintain accuracy levels above 90% and can efficiently reduce the total number of nodes by 59.09% in a large room (150 \({\mathrm{m}}^2\)) and by 68.75% in a small room (25 \({\mathrm{m}}^2\)). Furthermore, due to reduced nodes the proposed method can drastically reduce the needed amount of localization data and the hardware costs.