A CSI-Based Indoor Intrusion Detection and Localization Method

  • Xiaochao Dang
  • Caixia Li
  • Zhanjun HaoEmail author
  • Yuan Cao
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1101)


In this paper, we propose a method for indoor intrusion detection and localization that makes use of channel state information (CSI), which consists of an offline phase and an online phase. In the former, we collect CSI in different scenarios, and at different times, for more comprehensive characterization of signal propagation. To reduce the redundancy and dimensionality of CSI data, we employ the principal component analysis algorithm to extract the main features of CSI, and build the fingerprint database for localization. In the online phase, we first apply the earth mover’s distance algorithm to detect the presence of the person in the test area. Following this, we determine the approximate location of the target according to the change of CSI measurements, and compare this to the fingerprint database, to select reference points to build the sub-fingerprint database. Finally, we evaluate the actual position of this target using the improved k-Nearest Neighbor algorithm.


Channel state information Fingerprint database Intrusion detection Indoor localization 



This work was supported by the National Natural Science Foundation of China (Grant 61762079, 61662070), Key Science and Technology Support Program of Gansu Province (Grant 1604FKCA097, 17YF1GA015), Science and Technology Innovation Project of Gansu Province (Grant CX2JA037, 17CX2JA039).


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Xiaochao Dang
    • 1
    • 2
  • Caixia Li
    • 1
  • Zhanjun Hao
    • 1
    • 2
    Email author
  • Yuan Cao
    • 1
  1. 1.College of Computer Science and EngineeringNorthwest Normal UniversityLanzhouChina
  2. 2.Gansu Province Internet of Things Engineering Research CenterLanzhouChina

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