Radio Tomographic Imaging Based On Quartile Outliers Filter and PCA

Jun Lu, Wei Ke, Jie Jin, Yanli Wang

Abstract


Device-free wireless localization (DFL) that does not need the target equipped with any device is a new technique which could estimate the location by analyzing its shadowing effect on surrounding wireless links. This technique neither requires the target to be equipped with any device nor involves privacy concerns, which makes it an attractive and promising technique for many emerging smart applications. Therefore, how to characterize the influence of human behaviors is the key question. However, the distance estimation based on received signal strength indicator (RSSI) is easily affected by the temporal and spatial variance due to the multipath effect, which contributes to most of the estimation errors in current radio tomographic imaging (RTI) system. This paper proposes a device-free passive localization algorithm based on Quartile Outliers Filter (QOF) and Principal Component Analysis (PCA). In this work, we explore and exploit lower quartile and upper quartile of the original RSSI to identify and remove the outliers caused by the multipath effect or hardware facilities, and apply PCA to extract the most useful features. Extensive experiments performed in a clutter indoor laboratory and a building courtyard with 20 wireless nodes demonstrate that the outstanding performance of the proposed scheme.

Keywords


Radio tomographic imaging (RTI); Device-free localization (DFL); Quartile outliers filter (QOF); Principal component analysis (PCA)


DOI
10.12783/dtcse/wicom2018/26276

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