Shirong Li, Maosheng Fu, Xuemei Zhu, Fenghui Zhang, Fugui He
{"title":"Adaptive indoor positioning method based on direction discrimination and device conversion","authors":"Shirong Li, Maosheng Fu, Xuemei Zhu, Fenghui Zhang, Fugui He","doi":"10.1049/IET-WSS.2019.0079","DOIUrl":null,"url":null,"abstract":"Received signal strength (RSS) greatly differs due to the different occlusion directions and receiving device heterogeneity. It greatly affects the positioning accuracy. In this study, an adaptive indoor positioning method based on the direction discrimination and device conversion is proposed to solve these problems. This method is mainly composed of three parts: direction discrimination, device conversion and positioning models. First, the direction discrimination model can reduce the impact of a user's body occlusion. Best access points can be selected by principal component analysis to adapt to different directions and areas. Secondly, a device conversion model is used to reduce high offline work due to device heterogeneity. RSS of other devices can be converted to the value of one fixed device by least squares piecewise polynomial algorithm, without increasing the offline data collection workload. Finally, the results can be obtained by the positioning model. The problems of high dimensionality and non-linearity can be solved by the least squares support vector regression algorithm. Experimental results show that the proposed method can solve the problems of occlusion direction and device heterogeneity. The engineering applicability of positioning system can also be greatly improved.","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Wireless Sensor Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/IET-WSS.2019.0079","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Received signal strength (RSS) greatly differs due to the different occlusion directions and receiving device heterogeneity. It greatly affects the positioning accuracy. In this study, an adaptive indoor positioning method based on the direction discrimination and device conversion is proposed to solve these problems. This method is mainly composed of three parts: direction discrimination, device conversion and positioning models. First, the direction discrimination model can reduce the impact of a user's body occlusion. Best access points can be selected by principal component analysis to adapt to different directions and areas. Secondly, a device conversion model is used to reduce high offline work due to device heterogeneity. RSS of other devices can be converted to the value of one fixed device by least squares piecewise polynomial algorithm, without increasing the offline data collection workload. Finally, the results can be obtained by the positioning model. The problems of high dimensionality and non-linearity can be solved by the least squares support vector regression algorithm. Experimental results show that the proposed method can solve the problems of occlusion direction and device heterogeneity. The engineering applicability of positioning system can also be greatly improved.
期刊介绍：
IET Wireless Sensor Systems is aimed at the growing field of wireless sensor networks and distributed systems, which has been expanding rapidly in recent years and is evolving into a multi-billion dollar industry. The Journal has been launched to give a platform to researchers and academics in the field and is intended to cover the research, engineering, technological developments, innovative deployment of distributed sensor and actuator systems. Topics covered include, but are not limited to theoretical developments of: Innovative Architectures for Smart Sensors;Nano Sensors and Actuators Unstructured Networking; Cooperative and Clustering Distributed Sensors; Data Fusion for Distributed Sensors; Distributed Intelligence in Distributed Sensors; Energy Harvesting for and Lifetime of Smart Sensors and Actuators; Cross-Layer Design and Layer Optimisation in Distributed Sensors; Security, Trust and Dependability of Distributed Sensors. The Journal also covers; Innovative Services and Applications for: Monitoring: Health, Traffic, Weather and Toxins; Surveillance: Target Tracking and Localization; Observation: Global Resources and Geological Activities (Earth, Forest, Mines, Underwater); Industrial Applications of Distributed Sensors in Green and Agile Manufacturing; Sensor and RFID Applications of the Internet-of-Things ("IoT"); Smart Metering; Machine-to-Machine Communications.
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