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

Abstract

SUMMARYRadio 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.

Increasing LPWAN Scalability by Means of Concurrent Multiband IoT Technologies: An Industry 4.0 Use Case

“…• Multiradio development platforms: most scientific initiatives can be classified among those operating at 433 MHz and 2.4 GHz [33], [34], those operating at 868/920 MHz and 2.4 GHz [35]- [37], and those combining two different technologies at 2.4 GHz [38], [39]. 4…”