{"title":"船舶区域网络中ELCV三维定位算法研究","authors":"Liu Yang, Xia HaiRong, Wu Hua, Wu Xiaoming, Zhong Linghui, Xing Jinaping, Zhang Hui","doi":"10.11591/TELKOMNIKA.V11I6.2704","DOIUrl":null,"url":null,"abstract":"We propose a 3D localization algorithm used in ship area networks (SANs) in the literature before. In this paper in order to explore more performances of ELCV we made some other comprehensive simulations. In ELCV a classic noise model is introduced to characterize the acoustic background noise observed in SANs. Meanwhile random communication range nodes are placed in the SANs. ELCV is addressed to provide robust estimation of unknown nodes in the presence of outliers. In this algorithm sensor nodes are also equipped with random communication range that can be changed during a set scope. With ELCV, each individual unknown node will acquire data packages from anchors and then solve for a spatial node on some given point in cube space formed by eight neighbor anchors. With other three related anchor nodes around symmetric tetrahedron can be formed. Finally by centroid algorithm, in this symmetric tetrahedron, estimated node positions with accuracy and robustness are obtained. In this work more parameters are changed and different environment arguments are taken into account and then simulation results are given. By these simulation results we further prove the accuracy, efficiency and robustness in SANs. Meanwhile simulation processes are finished in MATLAB software. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2704 Full Text: PDF","PeriodicalId":414053,"journal":{"name":"TELKOMNIKA : Indonesian Journal of Electrical Engineering","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research of ELCV 3D Localization Algorithm in Ship Area Networks\",\"authors\":\"Liu Yang, Xia HaiRong, Wu Hua, Wu Xiaoming, Zhong Linghui, Xing Jinaping, Zhang Hui\",\"doi\":\"10.11591/TELKOMNIKA.V11I6.2704\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a 3D localization algorithm used in ship area networks (SANs) in the literature before. In this paper in order to explore more performances of ELCV we made some other comprehensive simulations. In ELCV a classic noise model is introduced to characterize the acoustic background noise observed in SANs. Meanwhile random communication range nodes are placed in the SANs. ELCV is addressed to provide robust estimation of unknown nodes in the presence of outliers. In this algorithm sensor nodes are also equipped with random communication range that can be changed during a set scope. With ELCV, each individual unknown node will acquire data packages from anchors and then solve for a spatial node on some given point in cube space formed by eight neighbor anchors. With other three related anchor nodes around symmetric tetrahedron can be formed. Finally by centroid algorithm, in this symmetric tetrahedron, estimated node positions with accuracy and robustness are obtained. In this work more parameters are changed and different environment arguments are taken into account and then simulation results are given. By these simulation results we further prove the accuracy, efficiency and robustness in SANs. Meanwhile simulation processes are finished in MATLAB software. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2704 Full Text: PDF\",\"PeriodicalId\":414053,\"journal\":{\"name\":\"TELKOMNIKA : Indonesian Journal of Electrical Engineering\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"TELKOMNIKA : Indonesian Journal of Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11591/TELKOMNIKA.V11I6.2704\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"TELKOMNIKA : Indonesian Journal of Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11591/TELKOMNIKA.V11I6.2704","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research of ELCV 3D Localization Algorithm in Ship Area Networks
We propose a 3D localization algorithm used in ship area networks (SANs) in the literature before. In this paper in order to explore more performances of ELCV we made some other comprehensive simulations. In ELCV a classic noise model is introduced to characterize the acoustic background noise observed in SANs. Meanwhile random communication range nodes are placed in the SANs. ELCV is addressed to provide robust estimation of unknown nodes in the presence of outliers. In this algorithm sensor nodes are also equipped with random communication range that can be changed during a set scope. With ELCV, each individual unknown node will acquire data packages from anchors and then solve for a spatial node on some given point in cube space formed by eight neighbor anchors. With other three related anchor nodes around symmetric tetrahedron can be formed. Finally by centroid algorithm, in this symmetric tetrahedron, estimated node positions with accuracy and robustness are obtained. In this work more parameters are changed and different environment arguments are taken into account and then simulation results are given. By these simulation results we further prove the accuracy, efficiency and robustness in SANs. Meanwhile simulation processes are finished in MATLAB software. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2704 Full Text: PDF