{"title":"使用启发式优化的基于加权可见性图的 WiFi 室内定位方法","authors":"Turan Goktug Altundogan, Mehmet Karaköse","doi":"10.55525/tjst.1254099","DOIUrl":null,"url":null,"abstract":"With the widespread use of wireless communication technologies and IoT applications, researchers are \ndeveloping approaches that utilize WiFi signals for indoor location determination. In this study, indoor positioning process \nbased on heuristic optimization-based methods was performed by creating weighted visibility matrices of access points based on WiFi signal strength (RSSI) values. In the proposed method, the PSO and GA approaches determine the position of the mobile user using a common fitness function based on the visibility weight matrices. The proposed method has been tested on a virtual scenario where position ranges based on RSSI ranges are determined. Both heuristic optimization methods are compared according to different criteria and the positioning process is performed with a maximum error of 3m for the GA based method and a maximum of 1.5m for the PSO based method.","PeriodicalId":516893,"journal":{"name":"Turkish Journal of Science and Technology","volume":"20 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Weighted Visibility Graph Based WiFi Indoor Positioning Method Using Heuristic Optimization\",\"authors\":\"Turan Goktug Altundogan, Mehmet Karaköse\",\"doi\":\"10.55525/tjst.1254099\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the widespread use of wireless communication technologies and IoT applications, researchers are \\ndeveloping approaches that utilize WiFi signals for indoor location determination. In this study, indoor positioning process \\nbased on heuristic optimization-based methods was performed by creating weighted visibility matrices of access points based on WiFi signal strength (RSSI) values. In the proposed method, the PSO and GA approaches determine the position of the mobile user using a common fitness function based on the visibility weight matrices. The proposed method has been tested on a virtual scenario where position ranges based on RSSI ranges are determined. Both heuristic optimization methods are compared according to different criteria and the positioning process is performed with a maximum error of 3m for the GA based method and a maximum of 1.5m for the PSO based method.\",\"PeriodicalId\":516893,\"journal\":{\"name\":\"Turkish Journal of Science and Technology\",\"volume\":\"20 11\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Turkish Journal of Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.55525/tjst.1254099\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Turkish Journal of Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.55525/tjst.1254099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
随着无线通信技术和物联网应用的广泛使用,研究人员正在开发利用 WiFi 信号确定室内位置的方法。在本研究中,通过根据 WiFi 信号强度(RSSI)值创建接入点的加权可见度矩阵,执行了基于启发式优化方法的室内定位过程。在所提出的方法中,PSO 和 GA 方法使用基于可见度加权矩阵的通用拟合函数确定移动用户的位置。所提出的方法已在一个虚拟场景中进行了测试,该场景中的位置范围是根据 RSSI 范围确定的。根据不同的标准对两种启发式优化方法进行了比较,定位过程中,基于 GA 的方法的最大误差为 3 米,基于 PSO 的方法的最大误差为 1.5 米。
Weighted Visibility Graph Based WiFi Indoor Positioning Method Using Heuristic Optimization
With the widespread use of wireless communication technologies and IoT applications, researchers are
developing approaches that utilize WiFi signals for indoor location determination. In this study, indoor positioning process
based on heuristic optimization-based methods was performed by creating weighted visibility matrices of access points based on WiFi signal strength (RSSI) values. In the proposed method, the PSO and GA approaches determine the position of the mobile user using a common fitness function based on the visibility weight matrices. The proposed method has been tested on a virtual scenario where position ranges based on RSSI ranges are determined. Both heuristic optimization methods are compared according to different criteria and the positioning process is performed with a maximum error of 3m for the GA based method and a maximum of 1.5m for the PSO based method.