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An Improved Fingerprint Algorithm with Access Point Selection and Reference Point Selection Strategies for Indoor Positioning

Published online by Cambridge University Press:  14 July 2020

Changgeng Li ,
Hui Huang  and
Bowen Liao
Changgeng Li*
Affiliation:
(School of Physics and Electronics, Central South University, Changsha, China)
Hui Huang
Affiliation:
(School of Physics and Electronics, Central South University, Changsha, China)
Bowen Liao
Affiliation:
(School of Physics and Electronics, Central South University, Changsha, China)
*
(E-mail: lcgeng@csu.edu.cn)
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Abstract

The fingerprint positioning (FP) algorithm has been investigated extensively owing to the fact that it can provide a relatively ideal indoor positioning result. However, the effectiveness of the fingerprint algorithm relies on the size of fingerprint database, which prevents the algorithm from being widely applied in practical applications. In this paper, an improved fingerprint algorithm with access point (AP) selection strategy and reference point (RP) selection strategy is proposed to reduce the size of the fingerprint database and improve the positioning accuracy. The experimental results show that the proposed algorithm can reduce the storage size of the fingerprint database by more than 42·64%. Moreover, compared with the FP algorithm, the fingerprint algorithm with segment characteristic distance (FP-SCD) and the fingerprint algorithm with RP selection strategy (FP-RPSS), the average positioning error of the proposed algorithm is reduced by 20·15%, 10·83% and 11·57%, respectively. Therefore, the proposed algorithm has a good application in real positioning scenarios.

Keywords

Indoor positioningFingerprint algorithmAP selection strategyRP selection strategy

Information

Type
Research Article
Information
The Journal of Navigation , Volume 73 , Issue 6 , November 2020 , pp. 1182 - 1201
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Copyright
Copyright © The Royal Institute of Navigation 2020

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