{"title":"基于压缩感知的无线传感器网络节点定位算法","authors":"Hongxu Tao, Yun Lin, Sen Wang","doi":"10.1109/apcap.2018.8538047","DOIUrl":null,"url":null,"abstract":"To obtain better performance and lower error localization algorithms, this paper proposes an algorithm based on Orthogonal Matching Pursuit (OMP) reconstruction and Basis Pursuit (BP) reconstruction algorithm for wireless sensor network node localization in combination with compressed sensing. These two algorithms both belong to the localization algorithm without ranging and meet three conditions when solving the problem of location algorithm which makes them more suitable for practical application. Compared with other existing range-free algorithms, such as the LSVM algorithm, the compressed sensing algorithm has better positioning performance. Therefore, the compressed sensing algorithm is a more reliable and practical positioning algorithm.","PeriodicalId":198124,"journal":{"name":"2018 IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Node Localization Algorithm for Wireless Sensor Network Based on Compressed Sensing\",\"authors\":\"Hongxu Tao, Yun Lin, Sen Wang\",\"doi\":\"10.1109/apcap.2018.8538047\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To obtain better performance and lower error localization algorithms, this paper proposes an algorithm based on Orthogonal Matching Pursuit (OMP) reconstruction and Basis Pursuit (BP) reconstruction algorithm for wireless sensor network node localization in combination with compressed sensing. These two algorithms both belong to the localization algorithm without ranging and meet three conditions when solving the problem of location algorithm which makes them more suitable for practical application. Compared with other existing range-free algorithms, such as the LSVM algorithm, the compressed sensing algorithm has better positioning performance. Therefore, the compressed sensing algorithm is a more reliable and practical positioning algorithm.\",\"PeriodicalId\":198124,\"journal\":{\"name\":\"2018 IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)\",\"volume\":\"70 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/apcap.2018.8538047\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/apcap.2018.8538047","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Node Localization Algorithm for Wireless Sensor Network Based on Compressed Sensing
To obtain better performance and lower error localization algorithms, this paper proposes an algorithm based on Orthogonal Matching Pursuit (OMP) reconstruction and Basis Pursuit (BP) reconstruction algorithm for wireless sensor network node localization in combination with compressed sensing. These two algorithms both belong to the localization algorithm without ranging and meet three conditions when solving the problem of location algorithm which makes them more suitable for practical application. Compared with other existing range-free algorithms, such as the LSVM algorithm, the compressed sensing algorithm has better positioning performance. Therefore, the compressed sensing algorithm is a more reliable and practical positioning algorithm.