Author:
Yu Xiao-min,Wang Hui-qiang,Wu Jin-qiu
Abstract
AbstractWith the development of network technology, WLAN-based indoor localization plays an increasingly important role. Most current localization methods are based on the comparison between the received signal strength indication (RSSI) and the RSS in the database, whose nearest reference point is the location point. However, since a uniform standard for measuring components of smartphones has not yet been established, the Wi-Fi chipsets on different smartphones may have different sensitivity levels to different Wi-Fi access points (APs) and channels. Even for the same signal, RSSI values obtained by different terminals at the same time and the same location may be different. Therefore, the impact of terminal heterogeneity on localization accuracy can be overlooked. To address this issue, a fusion method based on received signal strength difference and compressive sensing (RSSD-CS) is proposed in this paper, which can reduce the influence caused by the terminal heterogeneity. Besides, a fingerprint database is reconstructed from the existing reference point data. Experiments show that the proposed RSSD-CS algorithm can achieve high localization accuracy in indoor localization, and the accuracy is enhanced by 20.5% and 15.6% compared to SSD and CS algorithm.
Funder
National Natural Science Foundation of China
Science and Technology Major Project of China
China Postdoctoral Science Foundation
Natural science foundation of Heilongjiang Province of China
the Basic Business Project in Education Department of Heilongjiang Province of China
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Computer Science Applications,Signal Processing
Cited by
15 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献