{"title":"一种无线传感器网络自定位算法","authors":"Juelong Li, X. Du, Jianchun Xing, Qiliang Yang","doi":"10.1109/CCDC.2012.6243098","DOIUrl":null,"url":null,"abstract":"Considering the deficiencies and limitations of Multidimensional Scaling -based (MDS-MAP) localization algorithm, a new MDS-mass spring-based (MDS-MS) localization algorithm was proposed by analyzing the MDS-MAP algorithm and Mass Spring Optimization-based (MSO) positioning algorithm. Moreover, for different ranging error, network connectivity and anchor node density, MDS-MAP, MSO, MDS-MAP(P) and MDS-MS four localization algorithms were simulated and compared. The simulation results show that MDS-MS-based algorithm possesses strong robustness and high positioning precision, and is fit for localization in sparse network topology and irregular network topology.","PeriodicalId":345790,"journal":{"name":"2012 24th Chinese Control and Decision Conference (CCDC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A self-localization algorithm for wireless sensor networks\",\"authors\":\"Juelong Li, X. Du, Jianchun Xing, Qiliang Yang\",\"doi\":\"10.1109/CCDC.2012.6243098\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Considering the deficiencies and limitations of Multidimensional Scaling -based (MDS-MAP) localization algorithm, a new MDS-mass spring-based (MDS-MS) localization algorithm was proposed by analyzing the MDS-MAP algorithm and Mass Spring Optimization-based (MSO) positioning algorithm. Moreover, for different ranging error, network connectivity and anchor node density, MDS-MAP, MSO, MDS-MAP(P) and MDS-MS four localization algorithms were simulated and compared. The simulation results show that MDS-MS-based algorithm possesses strong robustness and high positioning precision, and is fit for localization in sparse network topology and irregular network topology.\",\"PeriodicalId\":345790,\"journal\":{\"name\":\"2012 24th Chinese Control and Decision Conference (CCDC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 24th Chinese Control and Decision Conference (CCDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCDC.2012.6243098\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 24th Chinese Control and Decision Conference (CCDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2012.6243098","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
针对基于多维尺度(MDS-MAP)定位算法的不足和局限性,通过分析MDS-MAP算法和基于质量弹簧优化(Mass Spring optimization based, MSO)定位算法,提出了一种新的基于mds -质量弹簧(MDS-MS)的定位算法。此外,针对不同的测距误差、网络连通性和锚节点密度,对MDS-MAP、MSO、MDS-MAP(P)和MDS-MS 4种定位算法进行了仿真比较。仿真结果表明,基于mds - ms的定位算法具有较强的鲁棒性和较高的定位精度,适合于稀疏网络拓扑和不规则网络拓扑的定位。
A self-localization algorithm for wireless sensor networks
Considering the deficiencies and limitations of Multidimensional Scaling -based (MDS-MAP) localization algorithm, a new MDS-mass spring-based (MDS-MS) localization algorithm was proposed by analyzing the MDS-MAP algorithm and Mass Spring Optimization-based (MSO) positioning algorithm. Moreover, for different ranging error, network connectivity and anchor node density, MDS-MAP, MSO, MDS-MAP(P) and MDS-MS four localization algorithms were simulated and compared. The simulation results show that MDS-MS-based algorithm possesses strong robustness and high positioning precision, and is fit for localization in sparse network topology and irregular network topology.