Fingerprint positioning based on piecewise filtering of received signal strength indices and space-scene constraints

Fingerprint positioning based on piecewise filtering of received signal strength indices and space-scene constraints

Yong ShiXianjian Xiao Fuqiang Lu Xiaofei Yang 

School of Computer Information and Engineering, Changzhou Institute of Technology, Changzhou 213032, China

Corresponding Author Email: 
shiy@czu.cn
Page: 
40-44
|
DOI: 
https://doi.org/10.18280/rces.050203
Received: 
November 17 2017
| |
Accepted: 
June 29 2018
| | Citation

OPEN ACCESS

Abstract: 

This paper aims to reduce the dimensionality in fingerprint algorithm and achieve the optimal positioning accuracy at the minimal cost. For these purposes, the piecewise feature of iBeacon signal transmission was taken as the filtering factor of fingerprint positioning and adopted to filter the received signal strength indices (RSSIs) collected in real time. Then, the related fingerprints were filtered into fragments for subsequent online matching. After that, the indoor space-scene was divided into passage and hall, and the relevant constraint factor and data structure were discussed for fingerprint indexing. On this basis, the author proposed a novel method to optimize fingerprint positioning considering RSSI filtering and space-scene constraints. The experiments on an office space-scene reveal that the proposed method achieved the same result as the traditional one using 88% shorter matching time. This research provides an efficient and accuracy way of fingerprint positioning.

Keywords: 

fingerprint positioning, piecewise filter, space-scene, received signal strength indices (RSSIs)

1. Introduction
2. Rssi Piecewise Filter
3. Space-Scene Constraints
4. Fingerprint Positioning Considering Rssi Piecewise Filtering and Space-Scene
5. Case Study
6. Conclusions
Acknowledgment

This Research is partially supported by National Natural Science Foundation of China (Grant No.41571382), Supported by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (Grant No. 15KJB170006, No.16KJB520003). Supported by Taizhou Science and technology support program of China (Grant No. TS201621), Supported by Changzhou Science and technology support program of China (Grant No. CE20172023). Supported by Collaborative Innovation Center of Changzhou Institute of Technology for Digital Information Technology, and supported by Excellent Scientific and Technological Innovation Team of Changzhou Institute of Technology.

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