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移动无线传感器网络采样区域自调整的MCL定位算法 被引量：3

Self-adjusting Sampling Area MCL Algorithm for Mobile WSNs
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摘要 定位技术是无线传感器网络中关键的支撑技术之一。现有的无线传感器网络定位算法大多是针对静态场景的,不能直接应用于移动无线传感器网络。针对移动无线传感器网络的特点,在深入分析现有蒙特卡洛算法的基础上,提出一种改进机制,即采样区域自调整的蒙特卡洛节点定位(SA_MCL)算法。该算法通过对节点历史位置信息插值模拟获得节点的运动速度和方向,目的是为了自动调整采样区域,从而提高定位精度。仿真结果表明,采用SA_MCL算法,节点的定位精度有较大提高。 Localization technology is one of the key supporting technologies in wireless sensor networks（WSNs）. Most existing localization algorithms in literature are designed for static WSNs. Thus, most of them cannot be applied to mo- bile WSNs. This work began with a thorough investigation of Monte Carlo Loealization algorithm. On this basis, we proposed a self-adjusting sampling area localization（SA_MCL） algorithm, in consideration of the characteristics of mo- bile sensor node. SA_MCL uses interpolation simulation method to process historical location information of a node. The purpose is to get the velocity and direction of the node, thereby improving positioning accuracy. Simulation results show that SA_MCL algorithm improves positioning accuracy of a node significantly.
作者 叶飞虎 沈航 曹磊 白光伟
机构地区 南京工业大学计算机科学与技术系 南京理工大学计算机科学与技术学院 南京大学计算机软件新技术国家重点实验室
出处 《计算机科学》 CSCD 北大核心 2011年第12期49-52,60,共5页 Computer Science
基金 国家自然科学基金项目(60673185,61073197) 江苏省自然科学基金项目(BK2010548) 南京大学计算机软件新技术国家重点实验室开放课题(KFKT2010B08)资助
关键词 移动无线传感器网络 定位 蒙特卡洛 采样区域 Mobile WSNs, Localization, Monte carlo, Sampling area
分类号 TP393 [自动化与计算机技术—计算机应用技术]
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参考文献13

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二级参考文献53

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计算机科学
2011年 第12期

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