[1]姚放吾 宋艳.WSN中一种基于重叠区域的蒙特卡罗定位算法[J].计算机技术与发展,2012,(05):165-168.
　YAO Fang-wu,SONG Yan.Monte Carlo Localization Based on Overlapping Area for WSN[J].,2012,(05):165-168.
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WSN中一种基于重叠区域的蒙特卡罗定位算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2012年05期
页码:
165-168
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Monte Carlo Localization Based on Overlapping Area for WSN
文章编号:
1673-629X（2012）05-0165-04
作者:
姚放吾1; 2 宋艳1
[1]南京邮电大学计算机学院[2]江苏省无线传感网高技术研究重点实验室
Author(s):
YAO Fang-wu;  SONG Yan
[1]College of Computer, Nanjing University of Posts and Telecommunications[2]Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks
关键词:
无线传感器网络; MCL; AMCB; 节点定位
Keywords:
wireless sensor network;  MCL ;  AMCB ;  node location
分类号:
TP301.6
文献标志码:
A
摘要:
随着传感器网络的发展，其定位技术的研究弓I起了人们极大的关注。但由于无线传感器网络在电源、计算能力及内存容量等方面的局限性，大部分定位算法消耗太多能量。文中在传统Monte CadoLocalization（MCL）算法基础上提出对其改进的定位算法，构建节点运动模型，并结合sample—adaptiv eMonte CarloLocalization Boxed（AMCB）算法，减少采样区域，并在维持定位精度的前提下减少能耗。最后分析模拟结果表明改进的算法在无线传感器网络中是可行的和有效的，且表现出了良好的性能
Abstract:
With the development of wireless sensor networks, the localization technology has aroused great concern. However, due to limi- tations of power, computation capability and storage resources in wireless sensor networks, the public key algorithms are generally consid- ered that consume too much energy. In this paper, propose and analyze an improved Monte Carlo Localization algorithm （MCL）. The node motion model, combined with sample-adaptive Monte Carlo Localization Boxed （AMCB） algorithm is established, which is used to filter more inaccurate location samples and reduce energy consumption under the premise of maintaining the positioning accuracy. Finally, the simulation results show that the proposed scheme is feasible and effective, and delivers better performance

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备注/Memo

备注/Memo:
江苏高校优势学科建设工程资助项目（yx002001）姚放吾（1953-），男，教授，硕士生导师，研究方向为并行计算及其体系结构、嵌入式技术、计算机在通信中的应用；宋艳（1986-），女，江苏南京人，硕士生，研究方向为计算机在通信中的应用
更新日期/Last Update: 1900-01-01