PSOSVRPos: WiFi indoor positioning using SVR optimized by PSO. (15th July 2023)
- Record Type:
- Journal Article
- Title:
- PSOSVRPos: WiFi indoor positioning using SVR optimized by PSO. (15th July 2023)
- Main Title:
- PSOSVRPos: WiFi indoor positioning using SVR optimized by PSO
- Authors:
- Bi, Jingxue
Zhao, Meiqi
Yao, Guobiao
Cao, Hongji
Feng, Yougui
Jiang, Hu
Chai, Dashuai - Abstract:
- Abstract: Wireless fidelity (WiFi) indoor positioning has attracted the attention of thousands of researchers. It faces many challenges, and the primary problem is the low positioning accuracy, which hinders its widespread applications. To improve the accuracy, we propose a WiFi indoor positioning algorithm based on support vector regression (SVR) optimized by particle swarm optimization (PSO), termed PSOSVRPos. SVR algorithm devotes itself to solving localization as a regression problem by building the mapping between signal features and spatial coordinates in high dimensional space. PSO algorithm concentrates on the global-optimal parameter estimation of the SVR model. The positioning experiment is conducted on an open dataset (1511 samples, 154 features). The PSOSVRPos algorithm could achieve positioning accuracy with a mean absolute error of 1.040 m, a root mean square error (RMSE) of 0.863 m and errors within 1 m of 59.8%. Experimental results indicate that the PSOSVRPos algorithm is a precise approach for WiFi indoor positioning as it reduces the RMSE (35%) and errors within 1 m (14%) compared with state-of-the-art algorithms such as convolutional neural network (CNN) based methods.
- Is Part Of:
- Expert systems with applications. Volume 222(2023)
- Journal:
- Expert systems with applications
- Issue:
- Volume 222(2023)
- Issue Display:
- Volume 222, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 222
- Issue:
- 2023
- Issue Sort Value:
- 2023-0222-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-07-15
- Subjects:
- WiFi -- Indoor positioning -- SVR -- PSO -- Parameter estimation -- CNN
Expert systems (Computer science) -- Periodicals
Systèmes experts (Informatique) -- Périodiques
Electronic journals
006.33 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09574174 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.eswa.2023.119778 ↗
- Languages:
- English
- ISSNs:
- 0957-4174
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3842.004220
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 26801.xml