Nothing blocks me: Precise and real-time LOS/NLOS path recognition in RFID systems

Shigeng Zhang, Chengwei Yang, Danming Jiang, Xiaoyan Kui, Song Guo, Albert Y. Zomaya, Jianxin Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

21 Citations (Scopus)


Radio frequency identification (RFID)-based localization and activity recognition have attracted much research attention recently. They rely on accurate measurements of signal features, e.g., phase and received signal strength (RSS), in line-of-sight (LOS) condition to estimate the location or activity status of the target objects. However, the LOS requirement might be frequently breached by obstacles between reader and tags in real deployed RFID systems. The resulting non-LOS (NLOS) signal will greatly reduce localization or activity recognition accuracy. How to filter out NLOS in the localization/activity recognition process is therefore practically important for guaranteeing accuracy. In this paper, we propose the first LOS/NLOS path recognition approach to differentiate the signals by LOS path from the ones by NLOS path. The proposed approach is both precise (with precision higher than 0.95) and real-time in nature (with recognition delay less than 400 ms) due to the following innovative designs. First, we design a new metric that can precisely distinguish LOS and NLOS paths by considering the joint variance of phase and RSS. Second, we propose an efficient method to mitigate the negative impacts of phase ambiguity on recognition precision. Third, we sample over a selected subset of channels and use only a handful of readings to perform LOS/NLOS path recognition, which greatly reduces the recognition delay without sacrificing precision. We conducted extensive experiments with commercial-off-the-shelf RFID devices. The results show that our approach achieves high precision and recall in all testing cases, with a precision of up to 0.969 and a recall of up to 0.991. Furthermore, our approach can also distinguish between different types of obstacles with an accuracy as high as 0.93.

Original languageEnglish
Article number8674553
Pages (from-to)5814-5824
Number of pages11
JournalIEEE Internet of Things Journal
Issue number3
Publication statusPublished - 1 Jun 2019


  • Line-of-sight/non-LOS (LOS/NLOS)
  • Path recognition
  • Radio frequency identification (RFID)
  • RFID localization
  • RFID tags

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications


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