B. Cheng, R. E. Hudson, F. Lorenzelli, L. Vandenberghe, Kung Yao
{"title":"Distributed Gauss-Newton method for node loclaization in wireless sensor networks","authors":"B. Cheng, R. E. Hudson, F. Lorenzelli, L. Vandenberghe, Kung Yao","doi":"10.1109/SPAWC.2005.1506273","DOIUrl":null,"url":null,"abstract":"We present distributed algorithms for sensor localization based on the Gauss-Newton method. Each sensor updates its estimated location by computing the Gauss-Newton step for a local cost function and choosing a proper step length. Then it transmits the updated estimate to all the neighboring sensors. The proposed algorithms provide non-increasing values of a global cost function. It is shown in the paper that the algorithms have computational complexity of O(n) per iteration and a reduced communication cost over centralized algorithms.","PeriodicalId":105190,"journal":{"name":"International Workshop on Signal Processing Advances in Wireless Communications","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Signal Processing Advances in Wireless Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPAWC.2005.1506273","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
We present distributed algorithms for sensor localization based on the Gauss-Newton method. Each sensor updates its estimated location by computing the Gauss-Newton step for a local cost function and choosing a proper step length. Then it transmits the updated estimate to all the neighboring sensors. The proposed algorithms provide non-increasing values of a global cost function. It is shown in the paper that the algorithms have computational complexity of O(n) per iteration and a reduced communication cost over centralized algorithms.