电子学报Issue(10)：2110-2116,7.DOI:10.3969/j.issn.0372-2112.2015.10.033
基于序列相关值的蒙特卡罗优化算法
Sequence Correlation Optimized Monte Carlo Localization
摘要
Abstract
Monte Carlo Localization(MCL)has a decisive role for the mobile nodes’localization in Wireless Sensor Net-works(WSN).In order to improve the positioning accuracy,an improved algorithm called Sequence Correlation Optimized Monte Carlo Localization(SCMCL)is proposed.Adopting the mobile node’s location based on the received signal strength indicator (RSSI)as the new sampling center,SCMCL can optimize the sampling area of MCL and etc.The signal values are stored as a target sequence,and by comparing the correlation values between samples’sequences and the target sequence,samples can be filtered out. Also the correlation values are used as the weighted standards to calculate coordinates of the mobile nodes.Extensive simulation re-sults confirm that the new localization approach outperforms MCL and etc.The SCMCL algorithm reduces the localization error by about 10% under the same density of beacon nodes and the maximum speed of mobile nodes.关键词
无线传感器网络/移动节点定位/蒙特卡罗/序列相关值Key words
wireless sensor networks/mobile nodes’localization/Monte Carlo/sequence correlation分类
信息技术与安全科学引用本文复制引用
刘志华,息珍珍,张双,陈嘉兴..基于序列相关值的蒙特卡罗优化算法[J].电子学报,2015,(10):2110-2116,7.基金项目
国家自然科学基金（No．61271125）；河北省自然科学基金（No．F2013205084）；河北省教育厅青年基金 （）
