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一种基于粒子滤波的WSN自适应定位算法

邓平,  伍小梅

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文章导航 > 西南交通大学学报  > 2014 >  27(2): 323-329.
邓平, 伍小梅. 一种基于粒子滤波的WSN自适应定位算法[J]. 西南交通大学学报, 2014, 27(2): 323-329. doi: 10.3969/j.issn.0258-2724.2014.02.021
引用本文: 邓平, 伍小梅. 一种基于粒子滤波的WSN自适应定位算法[J]. 西南交通大学学报, 2014, 27(2): 323-329. doi: 10.3969/j.issn.0258-2724.2014.02.021
shu
DENG Ping, WU Xiaomei. An Adaptive Localization Algorithm Based on Particle Filter for Wireless Sensor Networks[J]. Journal of Southwest Jiaotong University, 2014, 27(2): 323-329. doi: 10.3969/j.issn.0258-2724.2014.02.021
Citation: DENG Ping, WU Xiaomei. An Adaptive Localization Algorithm Based on Particle Filter for Wireless Sensor Networks[J]. Journal of Southwest Jiaotong University, 2014, 27(2): 323-329. doi: 10.3969/j.issn.0258-2724.2014.02.021
shu

一种基于粒子滤波的WSN自适应定位算法

doi: 10.3969/j.issn.0258-2724.2014.02.021
基金项目: 

国家自然科学基金资助项目（61071107）

详细信息
    作者简介:

    邓平（1964-），男，教授，博士，研究方向为无线网络定位技术、无线传感器网络，E-mail：pdeng@swjtu.edu.cn

An Adaptive Localization Algorithm Based on Particle Filter for Wireless Sensor Networks

    摘要
  • 摘要: 针对WSN节点定位问题中基于动态采样的AMCB算法在某些定位时刻粒子数过低，粒子的最优继承得不到保证的问题，提出了改进算法AMCB*.为解决AMCB算法在锚节点密度较低，节点所处网络状况不佳时定位精度不高的问题，提出一种基于粒子滤波的WSN自适应定位算法NAMCB，通过对节点所处的网络状况进行评估来设置合理的粒子数、定位方式与滤波条件.对80个节点连续定位125次的结果表明，NAMCB算法的平均定位误差为节点通信半径的0.344 2倍，平均采样次数为84次，相对于AMCB算法分别降低了12.26%与4.55%.

     

    Abstract: As the number of particles of the dynamic sampling based adaptive Monte Carlo boxed (AMCB) algorithm is too small at some localization time slots and the optimal inheritance of the particles can not be ensured, an improved particle filter localization algorithm named AMCB* was proposed. To solve the problem that the localization accuracy of the AMCB algorithm is low when the anchor node density is low and nodes are in bad network condition, an adaptive localization algorithm based on particle filter in WSN named NAMCB was proposed. NAMCB sets reasonable number of particles, localization mode and filtering condition based on the evaluation to the network condition of nodes at each localization time slot. In tests, when 80 nodes were continuously positioned 125 times, the average localization error of NAMCB was 0.344 2 times of node communication radius, and the average sampling number was 84. Compared with AMCB, both were reduced by 12.26% and 4.55% respectively.

     

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    • 参考文献(15)
  • 孙利民, 李建中, 陈渝, 等. 无线传感器网络[M]. 北京:清华大学出版社, 2005: 6-14.
    彭宇, 王丹. 无线传感器网络定位技术综述[J]. 电子测量与仪器学, 2011, 25(5): 389-399. PENG Yu, WANG Dan. A review: wireless sensor networks localization[J]. Journal of Electronic Measurement and Instrument, 2011, 25(5): 389-399.
    刘健, 沈海斌. 无线传感器网络的三围定位算法[J]. 控制器与微系统, 2013, 32(9): 66-70. LIU Jian, SHEN Haibin. Study on 3D localization algorithm for WSNs[J]. Transducer and Microsystem Technologies, 2013, 32(9): 66-70.
    刘繁明, 钱东, 刘超华. 一种人工物理优化的粒子滤波算法[J]. 控制与决策, 2012, 27(8): 1145-1156. LIU Fanming, QIAN Dong, LIU Chaohua. An artificial physics optimized particle filter[J]. Control and Decision, 2012, 27(8): 1145-1156.
    HU Lingxuan, EVANS D. Localization for mobile sensor networks//Proceeding of the Tenth International Conference on Mobile Computing and Networking. Philadelphia:, 2004: 45-57.
    BAGGIO A, LANGENDOEN K. Monte-Carlo localization for mobile wireless sensor networks//Second International Conference on Mobile Ad-hoc and Sensor Networks. Hong Kong:, 2006, 4325: 317-328.
    朱海平, 于红丞, 钟小勇, 等. 动态无线传感器网络的改进蒙特卡洛定位算法[J]. 传感技术学报, 2012, 25(9): 1284-1288. ZHU Haiping, YU Hongcheng, ZHONG Xiaoyong, et al. An improved Monte Carlo localization algorithm for mobile wireless sensor networks[J]. Chinese Journal of Sensors and Actuators, 2012, 25(9): 1284-1288.
    董齐芬, 俞立, 陈友荣, 等. 移动无线传感器网中的迭代蒙特卡洛定位算法研究[J]. 传感技术学报, 2012, 25(12): 1803-1808. DONG Qifen, YU Li, CHEN Yourong, et al. Interative Monte Carlo localization for mobile wireless sensor networks[J]. Chinese Journal of Sensors and Actuators, 2012, 25(12): 1803-1808.
    梅举, 陈涤, 辛玲. 基于蒙特卡洛方法的移动传感网节点定位优化算法[J]. 传感技术学报, 2013, 26(5): 689-693. MEI Ju, CHEN Di, XIN Ling. Optimized localization scheme for mobile wireless sensor networks based on Monte Carlo method[J]. Chinese Journal of Sensors and Actuators, 2013, 26(5): 689-693.
    刘志华, 李改燕, 刘晓爽. 基于最小二乘法的蒙特卡洛移动节点定位算法[J]. 传感技术学报, 2012, 25(4): 541-544. LIU Zhihua, LI Gaiyan, LIU Xiaoshuang. Monte-Carlo mobile node localization algorithms based on least squares method[J]. Chinese Journal of Sensors and Actuators, 2012, 25(4): 541-544.
    朱志宇, 苏岭东. 二进制无线传感器网络中的分布式自适应粒子滤波目标跟踪算法[J]. 计算机科学, 2013, 40(8): 43-45. ZHU Zhiyu, SU Lingdong. Target tracking based distribute adaptive particle filter in binary wireless sensor networks[J]. Computer Science, 2013, 40(8): 43-45.
    蒋鹏, 宋华华. 基于动态分簇路由优化和分布式粒子滤波的传感器网络目标跟踪算法[J]. 电子与信息学报, 2012, 34(9): 2187-2193. JIANG Peng, SONG Huahua. Target tracking algorithm for wireless sensor networks based on dynamic clister routing optimization and distributed particle filter[J]. Journal of Electronic Information Technology, 2012, 34(9): 2187-2193.
    AHMED N, RUTTEN M, BESSELL T, et al. Detection and tracking using particle-filter-based wireless sensor networks[J]. IEEE Transactions on Mobile Computing, 2010, 9(9): 1332-1345.
    LI Jun, XU Chen. An improved particle filter algorithm based on target tracking in wireless sensor network//International Conference on Communica-tions and Intelligence Information Security. Nanning: Computer Society, IEEE, 2010: 187-191.
    SOLTANINASAB B, SABAEI M, AMIRI J. Improving Monte Carlo localization algorithm using time series forecasting method and dynamic sampling in mobile WSNs//The Second International Conference on Communication Systems, Networks and Applications.Hong Kong:, 2010: 389-396.
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出版历程
  • 收稿日期:  2013-07-31
  • 刊出日期:  2014-03-25

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