[1]武加文,李光辉.基于GABP-KF的WSN数据漂移盲校准算法[J].智能系统学报,2019,14(02):254-262.[doi:10.11992/tis.201712003]
 WU Jiawen,LI Guanghui.GABP-KF-based blind calibration algorithm of data drift in wireless sensor networks[J].CAAI Transactions on Intelligent Systems,2019,14(02):254-262.[doi:10.11992/tis.201712003]
点击复制

基于GABP-KF的WSN数据漂移盲校准算法(/HTML)
分享到:

《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第14卷
期数:
2019年02期
页码:
254-262
栏目:
出版日期:
2019-03-05

文章信息/Info

Title:
GABP-KF-based blind calibration algorithm of data drift in wireless sensor networks
作者:
武加文12 李光辉123
1. 江南大学 物联网工程学院, 江苏 无锡 214122;
2. 物联网技术应用教育部工程技术研究中心, 江苏 无锡 214122;
3. 江苏省模式识别与计算智能工程实验室, 江苏 无锡 214122
Author(s):
WU Jiawen12 LI Guanghui123
1. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;
2. Research Center of IoT Technology Application Engineering (MOE), Wuxi 214122, China;
3. Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence, Wuxi 214122, China
关键词:
无线传感器网络数据漂移盲校准BP神经网络遗传算法卡尔曼滤波器去噪模型构建
Keywords:
wireless sensor networkdata driftblind correctionBP neural networkgenetic algorithmKalman filterdenoisingmodel building
分类号:
TP274.2
DOI:
10.11992/tis.201712003
摘要:
针对无线传感器网络节点容易产生数据漂移的问题,提出了一种新型的跟踪和校准节点数据流漂移的算法。首先使用基于遗传算法优化的BP神经网络对目标节点和其邻居节点间的时空相关性进行建模,以获得目标节点的预测值,再使用卡尔曼滤波器跟踪和校准该节点的数据漂移。针对不同的真实数据集进行仿真实验显示,该方法相较于其他对比方法模型预测精度更高,漂移校准性能更好。实验结果表明,该算法可以精确地校准传感器节点的数据漂移,提高节点数据的可靠性。
Abstract:
Data drifts easily occur in wireless sensor network. To solve this problem, we propose a novel algorithm for tracking and calibrating the drifts of sensor data stream. First, backpropagation (BP) neural network optimized by genetic algorithm is applied to model the spatio-temporal correlations between the target node and its neighbor nodes to predict the value of the node, and then, the data drift of the node is tracked and calibrated by a Kalman filter. The simulation results using different datasets demonstrate that this method has superior prediction accuracy and calibration performance, compared with other methods. The experimental results show that this method can accurately calibrate the sensor drift and improve the reliability of node data.

参考文献/References:

[1] WU Mou, TAN Liansheng, XIONG Naixue. Data prediction, compression, and recovery in clustered wireless sensor networks for environmental monitoring applications[J]. Information sciences, 2016, 329:800-818.
[2] KUMAR D, RAJASEGARAR S, PALANISWAMI M. Geospatial estimation-based auto drift correction in wireless sensor networks[J]. ACM transactions on sensor networks, 2015, 11(3):50.
[3] TAN Rui, XING Guoliang, YUAN Zhaohui, et al. System-level calibration for data fusion in wireless sensor networks[J]. ACM transactions on sensor networks, 2013, 9(3):28.
[4] RAMANATNAN N, BALZANO L, BURT M, et al. Rapid deployment with confidence:Calibration and fault detection in environmental sensor networks[R]. Technical Report CENS TR 62, Center for Embedded Networked Sensing, 2006.
[5] MILUZZO E, LANE N D, CAMPBELL A T, et al. CaliBree:A self-calibration system for mobile sensor networks[C]//Proceedings of the 4th IEEE International Conference on Distributed Computing in Sensor Systems. Berlin, Heidelberg, Germany:Springer-Verlag, 2008:314-331.
[6] TAYLOR C, RAHIMI A, BACHRACH J, et al. Simultaneous localization, calibration, and tracking in an ad hoc sensor network[C]//Proceedings of the 5th International Conference on Information Processing in Sensor Networks. Nashville, TN, USA:IEEE, 2006:27-33.
[7] LEE B T, SON S C, KANG K. A blind calibration scheme exploiting mutual calibration relationships for a dense mobile sensor network[J]. IEEE sensors journal, 2014, 14(5):1518-1526.
[8] BALZANO L, NOWAK R. Blind calibration of sensor networks[C]//Proceedings of the 6th International Conference on Information Processing in Sensor Networks. Cambridge, MA, USA:IEEE, 2007:79-88.
[9] LI Zhan, WANG Yuzhi, YANG Anqi, et al. Drift detection and calibration of sensor networks[C]//Proceedings of 2015 International Conference on Wireless Communications & Signal Processing. Nanjing, China:IEEE, 2015:1-6.
[10] WANG Yuzhi, YANG Anqi, LI Zhan, et al. Blind drift calibration of sensor networks using signal space projection and Kalman filter[C]//Proceedings of 2015 IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing. Singapore, Singapore:IEEE, 2015:1-6.
[11] TAKRURI M, ABOURA K, CHALLA S. Distributed recursive algorithm for auto calibration in drift aware wireless sensor networks[M]//ELLEITHY K. Innovations and Advanced Techniques in Systems, Computing Sciences and Software Engineering. Netherlands:Springer, 2008:21-25.
[12] TAKRURI M, RAJASEGARAR S, CHALLA S, et al. Online drift correction in wireless sensor networks using spatio-temporal modeling[C]//Proceedings of 200811th International Conference on Information Fusion. Cologne, Germany:IEEE, 2008:1-8.
[13] KUMAR D, RAJASEGARAR S, PALANISWAMI M. Automatic sensor drift detection and correction using spatial Kriging and Kalman filtering[C]//Proceedings of 2013 IEEE International Conference on Distributed Computing in Sensor Systems. Cambridge, MA, USA:IEEE, 2013:183-190.
[14] DING Shifei, SU Chunyang, YU Junzhao. An optimizing BP neural network algorithm based on genetic algorithm[J]. Artificial intelligence review, 2011, 36(2):153-162.
[15] 丁建立, 陈增强, 袁著祉. 遗传算法与蚂蚁算法的融合[J]. 计算机研究与发展, 2003, 40(9):1351-1356 DING Jianli, CHEN Zhenqiang, YUAN Zhuozhi. Genetic algorithm and ant algorithm fusion[J]. Journal of computer research and development, 2003, 40(9):1351-1356
[16] WELCH G, BISHOP G. An introduction to the Kalman filter[R]. Chapel Hill, NC, USA:University of North Carolina at Chapel Hill, 1995.
[17] 钟伟才, 刘静, 刘芳, 等. 二阶卡尔曼滤波分布估计算法[J]. 计算机学报, 2004, 27(9):1272-1277 ZHONG Weicai, LIU Jin, LIU Fang, et al. Second order estimation of distribution algorithms based on kalman filter[J]. Chinese journal of computers, 2004, 27(9):1272-1277
[18] TAKRURI M, RAJASEGARAR S, CHALLA S, et al. Spatio-temporal modelling-based drift-aware wireless sensor networks[J]. IET wireless sensor systems, 2011, 1(2):110-122.
[19] CHANG S G, YU Bin, VETTERLI M. Adaptive wavelet thresholding for image denoising and compression[J]. IEEE transactions on image processing, 2002, 9(9):1532-1546.

相似文献/References:

[1]毕晓君,张艳双.基于免疫算法的无线传感器网络路由算法[J].智能系统学报,2009,4(01):67.
 BI Xiao-jun,ZHANG Yan-shuang.A routing algorithm for wireless sensor networks based on an immune algorithm[J].CAAI Transactions on Intelligent Systems,2009,4(02):67.
[2]陈珍焰,刘贵喜.移动节点的LEACH改进型算法[J].智能系统学报,2008,3(02):140.
 CHEN Zhen-yan,LIU Gui-xi.An improved LEACH algorithm based on mobile sensor nodes[J].CAAI Transactions on Intelligent Systems,2008,3(02):140.
[3]海 丹,李 勇,张 辉,等.无线传感器网络环境下基于粒子滤波的移动机器人SLAM算法[J].智能系统学报,2010,5(05):425.[doi:10.3969/j.issn.1673-4785.2010.05.008]
 HAI Dan,LI Yong,ZHANG Hui,et al.Simultaneous localization and mapping of a mobile robot in wireless sensor networks based on particle filtering[J].CAAI Transactions on Intelligent Systems,2010,5(02):425.[doi:10.3969/j.issn.1673-4785.2010.05.008]
[4]何敏,赵东风,保利勇,等.一种能量有效的无线传感器网络轮询接入控制协议[J].智能系统学报,2012,7(03):265.
 HE Min,ZHAO Dongfeng,BAO Liyong,et al.An energyefficiency polling access control protocol for wireless sensor networks[J].CAAI Transactions on Intelligent Systems,2012,7(02):265.
[5]叶玲,李太华,代学武.无线传感器网络环境下基于卡尔曼滤波的PTP协议[J].智能系统学报,2012,7(06):518.
 YE Ling,LI Taihua,DAI Xuewu.Kalman filtering based precision time protocol (PTP) in wireless sensor networks[J].CAAI Transactions on Intelligent Systems,2012,7(02):518.
[6]梁俊斌,刘明.带时延约束的连通目标覆盖最大化生命周期问题[J].智能系统学报,2013,8(04):319.[doi:10.3969/j.issn.1673-4785.201304030]
 LIANG Junbin,LIU Ming.Lifetime maximization for delay constraint connected target coverage[J].CAAI Transactions on Intelligent Systems,2013,8(02):319.[doi:10.3969/j.issn.1673-4785.201304030]
[7]余华平,郭梅.面向管道系统的无线传感器网络三维节点部署算法[J].智能系统学报,2013,8(04):333.[doi:10.3969/j.issn.1673-4785.201304025]
 YU Huaping,GUO Mei.The research of three-dimensional node deployment of wireless sensor network for pipeline systems[J].CAAI Transactions on Intelligent Systems,2013,8(02):333.[doi:10.3969/j.issn.1673-4785.201304025]
[8]程磊,周明达,吴怀宇,等.无线传感器环境下粒子群优化的多机器人协同定位研究[J].智能系统学报,2015,10(01):138.[doi:10.3969/j.issn.1673-4785.201310067]
 CHENG Lei,ZHOU Mingda,WU Huaiyu,et al.Cooperative multi-robot localization based on particle swarm optimization in the environment of wireless sensor[J].CAAI Transactions on Intelligent Systems,2015,10(02):138.[doi:10.3969/j.issn.1673-4785.201310067]
[9]杨玉景,黄艺文,李太华,等.多跳无线传感器网络下基于KF优化的PTP协议[J].智能系统学报,2014,9(02):174.[doi:10.3969/j.issn.1673-4785.201310025]
 YANG Yujing,HUANG Yiwen,LI Taihua,et al.Precision time protocol (PTP) on the basis of Kalman filtering in the multi-hop wireless sensor network[J].CAAI Transactions on Intelligent Systems,2014,9(02):174.[doi:10.3969/j.issn.1673-4785.201310025]
[10]官铮,邹丹,丁洪伟,等.并行调度两级轮询控制传感器网络MAC协议分析[J].智能系统学报,2014,9(04):438.[doi:10.3969/j.issn.1673-4785.201304023]
 GUAN Zheng,ZOU Dan,DING Hongwei,et al.Study on parallel two-level polling control based MAC protocol for Wireless sensor networks[J].CAAI Transactions on Intelligent Systems,2014,9(02):438.[doi:10.3969/j.issn.1673-4785.201304023]

备注/Memo

备注/Memo:
收稿日期:2017-12-02。
基金项目:国家自然科学基金项目(61472368)、江苏省重点研发计划项目(BE2016627)、中央高校基本科研业务费项目(JUSRP51635B)、无锡市国际科技研发合作项目(CZE02H1706)、江苏省普通高校专业学位研究生实践创新计划项目(SJLX16_0499).
作者简介:武加文,男,1994年生,硕士研究生,主要研究方向为无线传感器网络数据漂移的检测与校准。;李光辉,男,1970年生,教授,博士生导师,博士,主要研究方向为无线传感器网络、无损检测技术等。主持国家863计划、国家自然科学基金重大研究项目、国家自然科学基金面上项目、科技部中小型企业创新基金及省部级科研项目15项。获得浙江省科技进步二等奖2项、省部级奖励3项、浙江省农机科技奖一等奖及浙江省“科技兴林”奖一等奖各1项,发表学术论文60余篇。
通讯作者:李光辉.E-mail:ghli@jiangnan.edu.cn
更新日期/Last Update: 2019-04-25