个人信息Personal Information
教授级高工
性别:女
毕业院校:大连理工大学
学位:博士
所在单位:控制科学与工程学院
电子邮箱:qhgao@dlut.edu.cn
Device-Free Activity Recognition Based on Coherence Histogram
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论文类型:期刊论文
发表时间:2019-02-01
发表刊物:IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
收录刊物:SCIE、EI
卷号:15
期号:2
页面范围:954-964
ISSN号:1551-3203
关键字:Activity recognition; coherence histogram; device free; wireless
摘要:Device-free activity recognition (DFAR) is a promising technique that detects the activity of a target by analyzing the influence of its existence on surrounding wireless links. It realizes target sensing without the participation or even awareness of the target. The key question of DFAR is how to characterize the influence of the target on wireless links. Existing works mostly utilize statistical features, such as mean and variance in time-domain, and energy as well as entropy in frequency-domain, to characterize the influenced signals. However, statistical features provide only partial information. This paper explores the method on how to characterize the distribution of the signal as a whole. Specifically, we present a novel coherence histogram, which leverages the spatial structural characteristics to better characterize the distribution of the wireless signal. The coherence histogram captures not only the occurrence probability of received signal strength (RSS) measurements, but also the spatial relationship between adjacent RSS measurements as well. Experimental results show that our coherence histogram-based DFAR system could achieve an accuracy of more than 96%, which significantly outperforms other state-of-the-art DFAR systems remarkably.