MuCHLoc: Indoor ZigBee Localization System Utilizing Inter-Channel Characteristics

Ryota Kimoto, Shigemi Ishida, Takahiro Yamamoto, Shigeaki Tagashira, Akira Fukuda

研究成果: ジャーナルへの寄稿学術誌査読

12 被引用数 (Scopus)


The deployment of a large-scale indoor sensor network faces a sensor localization problem because we need to manually locate significantly large numbers of sensors when Global Positioning System (GPS) is unavailable in an indoor environment. Fingerprinting localization is a popular indoor localization method relying on the received signal strength (RSS) of radio signals, which helps to solve the sensor localization problem. However, fingerprinting suffers from low accuracy because of an RSS instability, particularly in sensor localization, owing to low-power ZigBee modules used on sensor nodes. In this paper, we present MuCHLoc, a fingerprinting sensor localization system that improves the localization accuracy by utilizing channel diversity. The key idea of MuCHLoc is the extraction of channel diversity from the RSS of Wi-Fi access points (APs) measured on multiple ZigBee channels through fingerprinting localization. MuCHLoc overcomes the RSS instability by increasing the dimensions of the fingerprints using channel diversity. We conducted experiments collecting the RSS of Wi-Fi APs in a practical environment while switching the ZigBee channels, and evaluated the localization accuracy. The evaluations revealed that MuCHLoc improves the localization accuracy by approximately 15% compared to localization using a single channel. We also showed that MuCHLoc is effective in a dynamic radio environment where the radio propagation channel is unstable from the movement of objects including humans.

ジャーナルSensors (Basel, Switzerland)
出版ステータス出版済み - 4月 6 2019

!!!All Science Journal Classification (ASJC) codes

  • 分析化学
  • 原子分子物理学および光学
  • 生化学
  • 器械工学
  • 電子工学および電気工学


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