Open Access
ARTICLE
Research on Indoor Passive Positioning Technology Based on WiFi
Lei Sun1, Ling Tan1,*, Wenjie Ma1, Jingming Xia2
1 School of Computer and Software, Nanjing University of Information Science & Technology, Nanjing, China
2 School of Electronic & Information Engineering, Nanjing University of Information Science & Technology, Nanjing, China
* Corresponding Author: Ling Tan. Email:
Journal on Internet of Things 2020, 2(1), 23-35. https://doi.org/10.32604/jiot.2020.09075
Received 01 January 2020; Accepted 05 May 2020; Issue published 06 August 2020
Abstract
In recent years, WiFi indoor positioning technology has become a hot
research topic at home and abroad. However, at present, indoor positioning
technology still has many problems in terms of practicability and stability, which
seriously affects the accuracy of indoor positioning and increases the complexity of
the calculation process. Aiming at the instability of RSS and the more complicated
data processing, this paper proposes a low-frequency filtering method based on fast
data convergence. Low-frequency filtering uses MATLAB for data fitting to filter
out low-frequency data; data convergence combines the mean and multi-data
parallel analysis process to achieve a good balance between data volume and
system performance. At the same time, this paper combines the position fingerprint
and the relative position method in the algorithm, which reduces the error on the
algorithm system. The test results show that the strategy can meet the requirements
of indoor passive positioning and avoid a large amount of data collection and
processing, and the average positioning error is below 0.5 meters.
Keywords
Cite This Article
L. Sun, L. Tan, W. Ma and J. Xia, "Research on indoor passive positioning technology based on wifi,"
Journal on Internet of Things, vol. 2, no.1, pp. 23–35, 2020. https://doi.org/10.32604/jiot.2020.09075