Naigao Jin, Xinchaun Zhou, Chi Lin, Lei Wang, Yu Liu, Mathew L. Wymore, D. Qiao
{"title":"ThunderLoc: Smartphone-Based Crowdsensing for Thunder Localization","authors":"Naigao Jin, Xinchaun Zhou, Chi Lin, Lei Wang, Yu Liu, Mathew L. Wymore, D. Qiao","doi":"10.1109/SAHCN.2018.8397150","DOIUrl":null,"url":null,"abstract":"Thunder localization provides an important solution to lightning location systems. This paper designs a smartphone- based thunder localization system, ThunderLoc. The key idea is to turn the localization problem into search problem in Hamming space by collecting the dual-microphone data of smartphones via crowdsensing mechanism. We utilized the TDOA of dual- microphone integrated in smartphone. After the quantization with a bit for the TDOA measurement from the smartphone nodes, thunder localization is performed by minimizing the Hamming distance between the measured binary sequence and the binary vectors in a database. Evaluation results demonstrate that ThunderLoc can effectively localize the virtual thunder with good robustness.","PeriodicalId":139623,"journal":{"name":"2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAHCN.2018.8397150","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Thunder localization provides an important solution to lightning location systems. This paper designs a smartphone- based thunder localization system, ThunderLoc. The key idea is to turn the localization problem into search problem in Hamming space by collecting the dual-microphone data of smartphones via crowdsensing mechanism. We utilized the TDOA of dual- microphone integrated in smartphone. After the quantization with a bit for the TDOA measurement from the smartphone nodes, thunder localization is performed by minimizing the Hamming distance between the measured binary sequence and the binary vectors in a database. Evaluation results demonstrate that ThunderLoc can effectively localize the virtual thunder with good robustness.