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Journal Articles IEICE Transactions on Information and Systems Year : 2015

Dual-Band Sensor Network for Accurate Device-Free Localization in Indoor Environment with WiFi Interference

Abstract

Radio Frequency based Device-Free Localization (RFDFL) is an emerging localization technique without requirements of attaching any electronic device to a target. The target can be localized by means of measuring the shadowing of received signal strength caused by the target. However, the accuracy of RFDFL deteriorates seriously in environment with WiFi interference. State-of-the-art methods do not efficiently solve this problem. In this paper, we propose a dual-band method to improve the accuracy of RFDFL in environment without/with severe WiFi interference. We introduce an algorithm of fusing dual-band images in order to obtain an enhanced image inferring more precise location and propose a timestamp-based synchronization method to associate the dual-band images to ensure their one-one correspondence. With real-world experiments, we show that our method outperforms traditional single-band localization methods and improves the localization accuracy by up to 40.4% in real indoor environment with high WiFi interference.

Dates and versions

cea-01745398 , version 1 (28-03-2018)

Identifiers

Cite

Manyi Wang, Zhonglei Wang, Enjie Ding, Yun Yang. Dual-Band Sensor Network for Accurate Device-Free Localization in Indoor Environment with WiFi Interference. IEICE Transactions on Information and Systems, 2015, E98D (3), pp.596-606. ⟨10.1587/transinf.2014NTP0007⟩. ⟨cea-01745398⟩
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