{"title":"基于绕行路径角度信息的距离自由定位与最后一跳RSSI测量的距离计算","authors":"A. Paul, M. Arifuzzaman, Keping Yu, Takuro Sato","doi":"10.23919/ICMU48249.2019.9006644","DOIUrl":null,"url":null,"abstract":"The location estimation accuracy of range-free localization (RFL) is a crucial issue in Wireless Sensor Networks (WSNs). The accuracy has significant impact on localization dependent routing protocols and applications. The assumption that the sensor nodes are deployed in regular areas without any obstacles do not match the practical deployment scenarios, especially for scenarios like outdoor deployment of WSNs. In this paper, we propose a hybrid solution by combining a RFL method and range-based localization (RBL) method namely Received Signal Strength Indication (RSSI) to tackle the detoured path between sensors in anisotropic network and to combat the last hop distance calculation problem respectively. As a result, our hybrid approach significantly improves the localization accuracy in anisotropic network as compared to range free method only. We calculate the average hop distance (AHD) of detoured path by estimating the angle of the middle of the transmission path between every two anchor pairs one by one. The AHD is finally adjusted by estimating the RSSI based last hop distance measurement. Based on the simulation results, it is observed that our hybrid approach with few anchor nodes outperforms other RFL algorithms in anisotropic network and indicates an improvement in the localization accuracy.","PeriodicalId":348402,"journal":{"name":"2019 Twelfth International Conference on Mobile Computing and Ubiquitous Network (ICMU)","volume":"177 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Detour Path Angular Information based Range Free Localization with Last Hop RSSI Measurement based Distance Calculation\",\"authors\":\"A. Paul, M. Arifuzzaman, Keping Yu, Takuro Sato\",\"doi\":\"10.23919/ICMU48249.2019.9006644\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The location estimation accuracy of range-free localization (RFL) is a crucial issue in Wireless Sensor Networks (WSNs). The accuracy has significant impact on localization dependent routing protocols and applications. The assumption that the sensor nodes are deployed in regular areas without any obstacles do not match the practical deployment scenarios, especially for scenarios like outdoor deployment of WSNs. In this paper, we propose a hybrid solution by combining a RFL method and range-based localization (RBL) method namely Received Signal Strength Indication (RSSI) to tackle the detoured path between sensors in anisotropic network and to combat the last hop distance calculation problem respectively. As a result, our hybrid approach significantly improves the localization accuracy in anisotropic network as compared to range free method only. We calculate the average hop distance (AHD) of detoured path by estimating the angle of the middle of the transmission path between every two anchor pairs one by one. The AHD is finally adjusted by estimating the RSSI based last hop distance measurement. Based on the simulation results, it is observed that our hybrid approach with few anchor nodes outperforms other RFL algorithms in anisotropic network and indicates an improvement in the localization accuracy.\",\"PeriodicalId\":348402,\"journal\":{\"name\":\"2019 Twelfth International Conference on Mobile Computing and Ubiquitous Network (ICMU)\",\"volume\":\"177 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Twelfth International Conference on Mobile Computing and Ubiquitous Network (ICMU)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ICMU48249.2019.9006644\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Twelfth International Conference on Mobile Computing and Ubiquitous Network (ICMU)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ICMU48249.2019.9006644","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detour Path Angular Information based Range Free Localization with Last Hop RSSI Measurement based Distance Calculation
The location estimation accuracy of range-free localization (RFL) is a crucial issue in Wireless Sensor Networks (WSNs). The accuracy has significant impact on localization dependent routing protocols and applications. The assumption that the sensor nodes are deployed in regular areas without any obstacles do not match the practical deployment scenarios, especially for scenarios like outdoor deployment of WSNs. In this paper, we propose a hybrid solution by combining a RFL method and range-based localization (RBL) method namely Received Signal Strength Indication (RSSI) to tackle the detoured path between sensors in anisotropic network and to combat the last hop distance calculation problem respectively. As a result, our hybrid approach significantly improves the localization accuracy in anisotropic network as compared to range free method only. We calculate the average hop distance (AHD) of detoured path by estimating the angle of the middle of the transmission path between every two anchor pairs one by one. The AHD is finally adjusted by estimating the RSSI based last hop distance measurement. Based on the simulation results, it is observed that our hybrid approach with few anchor nodes outperforms other RFL algorithms in anisotropic network and indicates an improvement in the localization accuracy.