{"title":"基于改进子空间方法的无线传感器网络自定位","authors":"Liu Hongbo, Zhang Wei","doi":"10.1109/AICCSA.2008.4493556","DOIUrl":null,"url":null,"abstract":"In this paper, an improved subspace approach based on range measurement is proposed and analyzed. Through the factorization of multidimensional similarity (MDS) matrix, we derive a novel kernel subspace to estimate the coordinate of unknown mobile node in wireless sensor networks (WSN). Simulation results are included to contrast the estimator performance with general subspace method, and the performance analysis is provided.","PeriodicalId":234556,"journal":{"name":"2008 IEEE/ACS International Conference on Computer Systems and Applications","volume":"267 1-4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Self-localization based on improved subspace approach in wireless sensor network\",\"authors\":\"Liu Hongbo, Zhang Wei\",\"doi\":\"10.1109/AICCSA.2008.4493556\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an improved subspace approach based on range measurement is proposed and analyzed. Through the factorization of multidimensional similarity (MDS) matrix, we derive a novel kernel subspace to estimate the coordinate of unknown mobile node in wireless sensor networks (WSN). Simulation results are included to contrast the estimator performance with general subspace method, and the performance analysis is provided.\",\"PeriodicalId\":234556,\"journal\":{\"name\":\"2008 IEEE/ACS International Conference on Computer Systems and Applications\",\"volume\":\"267 1-4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE/ACS International Conference on Computer Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AICCSA.2008.4493556\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE/ACS International Conference on Computer Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICCSA.2008.4493556","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Self-localization based on improved subspace approach in wireless sensor network
In this paper, an improved subspace approach based on range measurement is proposed and analyzed. Through the factorization of multidimensional similarity (MDS) matrix, we derive a novel kernel subspace to estimate the coordinate of unknown mobile node in wireless sensor networks (WSN). Simulation results are included to contrast the estimator performance with general subspace method, and the performance analysis is provided.