Integrated positioning algorithm based on GPS/WLAN. (1st April 2019)

• Record Type: Journal Article
• Authors: Li, Dengao; Wei, Zheng; Zhao, Jumin; Cheng, Junbing; Ma, Zhiying
• Is Part Of: Concurrency and computation. Volume 31:Number 17(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-04-01
• Subjects: Federated Kalman filter -- GPS/WLAN -- information fusion -- particle filter; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.5277
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: In complex urban environment, GPS signals are susceptible to occlusion and interference; the positioning accuracy will be reduced or even impossible to locate. Today, Wireless Local Area Network (WLAN) localization technology can effectively supplement the blind spot of GPS signals. However, due to the instability of received signal strength (RSS), the positioning accuracy of WLAN is seriously affected. To solve the aforementioned problems, a GPS/WLAN integrated location algorithm based on particle filter is proposed. In our method, the federated Kalman filter is used to fuse the location information of GPS and WLAN, and then the important sampling function of the particle filter is generated by the fusion result. The updating of the particle weights is accomplished by the results of federated Kalman filter and map information. With the complementary characteristics of GPS and WLAN positioning technology, the experimental results show that our algorithm can effectively improves the coverage rate of GPS and the positioning accuracy of pedestrians in complex urban environment. Compared with GPS and WLAN single system and traditional fusion algorithm, the positioning accuracy of the proposed algorithm is significantly improved.