Rencheng Jin, Hao Xu, Ning Wei, Lisha Meng, Liding Wang
{"title":"A research on discrete probability estimate (DPE) localization algorithm in wireless sensor networks","authors":"Rencheng Jin, Hao Xu, Ning Wei, Lisha Meng, Liding Wang","doi":"10.1109/ICICIP.2012.6391444","DOIUrl":null,"url":null,"abstract":"This paper, from the law of normal distribution, we try some new methods of data acquisition and processing. Through depth analysis of probability distribution mechanism, this paper presents that we can use the rectangular area to replace the overlap regions. Through rasterization method, a kind of discrete probability estimate localization algorithm is established. In reducing the calculation of the node as far as possible, the new algorithm is easy to understanding and application, which overcome shortcomings of continuous probability distribution algorithm. Experiment results show that the algorithm we proposed in the paper has better location performance, compared with the typical location algorithm.","PeriodicalId":376265,"journal":{"name":"2012 Third International Conference on Intelligent Control and Information Processing","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Third International Conference on Intelligent Control and Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICIP.2012.6391444","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper, from the law of normal distribution, we try some new methods of data acquisition and processing. Through depth analysis of probability distribution mechanism, this paper presents that we can use the rectangular area to replace the overlap regions. Through rasterization method, a kind of discrete probability estimate localization algorithm is established. In reducing the calculation of the node as far as possible, the new algorithm is easy to understanding and application, which overcome shortcomings of continuous probability distribution algorithm. Experiment results show that the algorithm we proposed in the paper has better location performance, compared with the typical location algorithm.