Open AccessA New Algorithm for Indoor RSSI Radio Map Reconstruction
Author(s) -
Weixing Xue,
Qingquan Li,
Xianghong Hua,
Kegen Yu,
Weining Qiu,
Baoding Zhou
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2882379
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
This paper proposes an empirical model of RSSI radio map in order to improve the indoor positioning accuracy of Wi-Fi RSSI. First, the signal feature point in RSSI space is proposed based on the indoor RSSI map, which is similar to the geomorphic feature point in a topographic map. Then, we utilize a small amount of the grid points in geometric space to fill the RSSI grid network by using the theory of low rank matrix. Finally, a new algorithm for indoor RSSI radio map reconstruction has been proposed. Both the grid point in geometric space and the signal feature point in RSSI space have been utilized in the reconstruction of the RSSI empirical model, and different types of feature points have been weighted based on their corresponding positioning accuracy. The proposed algorithm was tested by experiments conducted within a room, and the results indicate that the proposed method significantly outperforms the traditional grid network algorithm.
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