Fingerprinting Positioning Algorithm for WiFi Based on Locally Weighted Regression and Support Vector Regression Optimized by Artificial Bee Colony

Authors

Wang Yan, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China;
Fucheng Yin, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China;
Zhicheng Ji, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China;
Dahu Yan, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China;

Abstract

Abstract: Since the traditional location fingerprinting algorithms have poor positioning accuracy and cost laborious efforts constructing fingerprinting database during the offline phase, a novel LWR-ABCSVR positioning algorithm was proposed, that the derived algorithm was based on the locally weighted regression (LWR) method and support vector regression was optimized by artificial bee colony (ABCSVR) algorithm. By using the proposed algorithm, the fingerprinting database was expanded by LWR step. The ABCSVR algorithm was employed to build the nonlinear relationship between the RSS values of reference points and their locations. The position of mobile terminal was predicted by the constructed model. Simulation results indicate that the proposed algorithm performs better than traditional location fingerprinting algorithms, in terms of positioning accuracy and database constructing costs.

Recommended Citation

Yan, Wang; Yin, Fucheng; Ji, Zhicheng; and Yan, Dahu (2020) "Fingerprinting Positioning Algorithm for WiFi Based on Locally Weighted Regression and Support Vector Regression Optimized by Artificial Bee Colony," Journal of System Simulation: Vol. 29: Iss. 6, Article 5.
DOI: 10.16182/j.issn1004731x.joss.201706005
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss6/5

First Page

1193

Revised Date

2016-11-08

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201706005

Last Page

1200

CLC

TP391.9

Recommended Citation

Wang Yan, Yin Fucheng, Ji Zhicheng, Yan Dahu. Fingerprinting Positioning Algorithm for WiFi Based on Locally Weighted Regression and Support Vector Regression Optimized by Artificial Bee Colony[J]. Journal of System Simulation, 2017, 29(6): 1193-1200.

DOI

10.16182/j.issn1004731x.joss.201706005