一种用于无线传感器网络三维定位的迭代估计方法

doi:10.11896/jsjkx.181001855

摘要/Abstract

摘要： 现有无线传感器网络三维定位算法大部分借鉴并基于相对成熟并且算法性能较好的二维定位算法原理,将其扩展至三维空间以实现节点定位,相比二维定位算法具有更好的定位精度。基于质心迭代估计的无线传感器网络二维定位算法通过对连通锚节点所围成平面的质心进行迭代计算,缩小了未知节点所在二维平面的范围,提高了节点的定位精度。基于此二维定位方法的原理,提出了一种用于无线传感器网络三维定位的迭代估计方法。首先,该算法计算当前连通锚节点所张成三维空间的质心坐标及其与未知节点间的接收信号强度;其次,以该质心节点为虚拟锚节点替代距离未知节点最远的连通锚节点,为未知节点自身的定位提供帮助。由于节点定位精度随着未知节点所处三维空间范围的缩小而不断提高,因此通过多次迭代后可以获得理想的定位精度。在3.50GHz电脑平台上模拟实际无线传感器网络环境,利用交互式数据语言对所提算法进行仿真,以验证算法的性能。仿真结果表明,所提算法与基于质心迭代估计的无线传感器网络二维定位算法相比,其定位精度可提高3%~6%;与三维质心定位算法相比,其定位精度可提高5%~23%。同时,所提算法具有较好的抗RSSI测量误差的能力,并通过多次迭代定位使得节点定位覆盖率可以达到99%以上,是一种适用于无线传感器网络三维定位的有效方法。

关键词: 非测距, 三维节点定位, 无线传感器网络, 质心定位

Abstract: The existing three-dimension localization algorithm for wireless sensor networks (WSN) is mostly based on the principle of two-dimension localization algorithm with mature and good performance.Compared with the two-dimensional localization algorithm,most of the three-dimension localization algorithms have better localization accuracy.Two-dimensional localization algorithm for wireless sensor networks based on centroid iteration estimation reduces the range of two-dimensional plane of unknown nodes and improves the positioning accuracy of nodes by iterating the centroid of the plane surrounded by connected anchor nodes.Based on the theory of the two-dimension centroid localization algorithm,this paper proposed a novel approach of three-dimensional node localization algorithm based on iterative computation.First,the centroid coordinates of the three-dimensional space enclosed by the current connected anchor nodes as well as the received signal strength (RSSI) between the unknown node and the centroid node are calculated.Then,the current connected anchor node with the weakest RSSI is replaced with the centroid node in order to reduce the three-dimensional space enclosed by the connected anchor nodes.The location accuracy can be improved through multi-itera-tions with an appropriate threshold.Simulation results are obtained with interactive data language (IDL) on a PC of 3.50GHz.Judging from the simulation results,there is an improvement of 3% to 6% in location accuracy compared with the two-dimension localization algorithm,and an improvement of 5% to 23% in location accuracy compared with the 3D centroid localization algorithm.What’s more,the proposed algorithm performs well for RSSI error disturbance and can reach more than 99% of localization coverage after multi-iterations.

Key words: 3D node self-localization, Centroid localization, Range-free, Wireless sensor networks

中图分类号:

TP393

蒋锐, 吴谦, 徐友云. 一种用于无线传感器网络三维定位的迭代估计方法[J]. 计算机科学, 2019, 46(11): 65-71. https://doi.org/10.11896/jsjkx.181001855

JIANG Rui, WU Qian, XU You-yun. 3D Node Localization Algorithm Based on Iterative Computation for Wireless Sensor Network[J]. Computer Science, 2019, 46(11): 65-71. https://doi.org/10.11896/jsjkx.181001855

参考文献

[1]刘伟荣,何云.物联网与无线传感器网络 [M].北京:电子工业出版社,2013:140.
[2]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,2005:135.
[3]YAGHOUBI F,ABBASFAR A A,MAHAM B.Energy-efficient RSSI-based localization for wireless sensor networks [J].IEEE Communications Letters,2014,18(6):973-976.
[4]SAHOTA H,KUMAR R.Maximum-likelihood sensor node localization using received signal strength in multimedia with multipath characteristics [J].IEEE Systems Journal,2018,12(1):506-515.
[5]ZHANG Y Y,XING S,ZHU Y P,et al.RSS-based localization in WSNs using gaussian mixture model via semidefinite relaxation [J].IEEE Communications Letters,2017,21(6):1329-1332.
[6]SAHU P K,WU E H K,SAHOO J.DuRT:Dual RSSI trend based localization for wireless sensor networks [J].IEEE Sensors Journal,2013,13(8):3115-3123.
[7]YU K,GUO Y J,HEDLEY M.TOA-based distributed localisation with unknown internal delays and clock frequency offsets in wireless sensor networks [J].IET Signal Processing,2009,3(2):106-118.
[8]XU E,DING Z,DASGUPTA S.Source localization in wirelesssensor networks from signal time-of-arrival measurements [J].IEEE Transactions on Signal Processing,2011,59(6):2887-2897.
[9]BANDIERA F,COLICCIA A,RICCI G,et al.TDOA localization in asynchronous WSNs [C]∥12th IEEE International Conference on Embedded and Ubiquitous Computing (EUC).Milan:IEEE Computer Society,2014:193-196.
[10]SUN D Y,QIAN Z H,HAN M F,et al.Improving multilateration algorithm by cluster analysis in WSN [J].Acta Electronica Sinica,2014,42(8):1601-1607.(in Chinese)
孙大洋,钱志鸿,韩梦飞,等.无线传感器网络中多边定位的聚类分析改进算法 [J].电子学报,2014,42(8):1601-1607.
[11]SLAVISA T,MARKO B,RUI D,et al.RSS-Based Localization in Wireless Sensor Networks Using Convex Relaxation:Noncooperative and Cooperative Schemes [J].IEEE Transactions on Vehicular Technology,2015,64(5):2037-2050.
[12] NINIPAMA B,JOHN H,DEBORAH F.GPS-less low cost outdoor localization for very small devices [J].IEEE Personal Communications,2000,7(5):28-34.
[13] HADIR A,ZINE D K,BAKHOUYA M,et al.An optimizedDV-hop localization algorithm using average hop weighted mean in WSNs [C]∥5th Workshop on Codes,Cryptography and Communication Systems (WCCCS).El Jadida:Chouaib Doukkali University,2014:25-29.
[14] XIANG J,TAN W W.An improved DV-hop algorithm based on iterative computation for wireless sensor network localization [C]∥2013 IEEE International Workshop on Electromagnetics (iWEM).Hongkong:IEEE Press,2013:171-174.
[15] ZHOU Y,AO X,XIA S X.An improved APIT node self-localization algorithm in WSN[C]∥7th World Congress on Intelligent Control and Automation (WCICA).Changsha:IEEE Control System Society,2018:193-196.
[16] WANG J Z,JIN H X.Improvement on APIT localization algorithms for wireless sensor networks [C]∥International Conference on Networks Security,Wireless Communications and Trusted Computing (NSWCTC).Wuhan:IEEE Computer Society,2009:719-723.
[17] DOHERTY L,PISTER K S J,GHAOUI L E.Convex position estimation in wireless sensor networks [C]∥Proc of Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies.Anchorage:IEEE Press,2001:1655-1663.
[18]GUADANE M,BCHIMI W,SAMET A,et al.Enhanced range-free localization in wireless sensor networks using a new weighted hop-size estimation technique [C]∥IEEE 28th Annual International Symposium on Personal,Indoor,and Mobile Radio Communications (PIMRC).Montreal:IEEE Press,2017:1-5.
[19]MENG Y H,WEN Y Y,CHEN J,et al.Range-free localization algorithm based on proximity for wireless sensor networks [J].Acta Electronica Sinica,2014,42(9):1712-1717.(in Chinese)
孟颍辉,闻英友,陈剑,等.无线传感器网络中基于接近度的无需测距定位算法[J].电子学报,2014,42(9):1712-1717.
[20]DWIVEDI A,VAMSI P R.Performance analysis of range free localization methods for wireless sensor networks [C]∥4th International Conference on Signal Processing,Computing and Control (ISPCC).Heraklion:IEEE Press,2017:521-526.
[21] ANTHRAYOSE S,PAYAL A.Comparative analysis of approximate point in triangulation (APIT) and DV-hop algorithms for solving localization problem in wireless sensor networks [C]∥IEEE 7th International Advance Computing Conference (IACC).Marina:IEEE Computer Society,2017:372-378.
[22] LIANG J L,SHAO J,XU Y,et al.Sensor network localization in constrained 3-D spaces[C]∥Proceeding of the IEEE International Conference on Mechatronics and Antomation.Harbin:IEEE Press,2006:49-54.
[23] FANG W S,LUO Y Z,HUANG Y.Three-Dimensional DVHop location technology for coal mine based on WSNs [C]∥IEEE International Conference on Computational Science and Engineering (CSE) and Embedded and Ubiquitous Computing (EUC).Guangzhou:IEEE Press,2017:22-25.
[24]WANG D.Node self-localization algorithm for 3D wireless sensor networks [D].Chengdu:Southwest Jiaotong University,2007.(in Chinese)
王丹.三维无线传感器网络节点自定位算法研究[D].成都:西南交通大学,2007.
[25]LIU Y H,PU J H,HE Y,et al.Three-dimensional self-localization scheme for wireless sensor networks[J].Journal of Beijing University of Aeronautics and Astronautics,2008,34(6):647-651.(in Chinese)
刘玉恒,蒲菊华,赫阳,等.无线传感器网络三维自身定位方法[J].北京航空航天大学学报,2008,34(6):647-651.
[26]TANG L R,GONG Y,LUO Y T,et al.A 3D position algorithm based on euclidean for wireless sensor networks [J].Acta Electronica Sinica,2012,40(4):821-825.(in Chinese)
唐良瑞,宫月,罗艺婷,等.一种基于Euclidean的无线传感器网络三维定位算法 [J].电子学报,2012,40(4):821-825.
[27]JIANG R,YANG Z.An improved centroid localization algorithm based on iterative computation for wireless sensor network [J].Acta Physica Sinica,2016,65(3):030101.1-030101.9.(in Chinese)
蒋锐,杨震.基于质心迭代估计的无线传感器网络节点定位算法 [J].物理学报,2016,65(3):030101.1-030101.9.
[28]MADDUMABANDARA A,LEUNG H,LIU M.Experimental evaluation of indoor localization using wireless sensor networks [J].IEEE Sensors Journal,2015,15(9):5228-5237.

相关文章 15

[1]	范星泽, 禹梅. 改进灰狼算法的无线传感器网络覆盖优化 Coverage Optimization of WSN Based on Improved Grey Wolf Optimizer 计算机科学, 2022, 49(6A): 628-631. https://doi.org/10.11896/jsjkx.210500037
[2]	王国武, 陈元琰. 基于跳数修正和遗传模拟退火优化DV-Hop定位算法 Improvement of DV-Hop Location Algorithm Based on Hop Correction and Genetic Simulated Annealing Algorithm 计算机科学, 2021, 48(6A): 313-316. https://doi.org/10.11896/jsjkx.201000101
[3]	王栋, 王虎, 姜迁里. 基于6LoWPAN的低功耗长距离海洋环境监测系统 Low Power Long Distance Marine Environment Monitoring System Based on 6LoWPAN 计算机科学, 2020, 47(6A): 596-598. https://doi.org/10.11896/JsJkx.190900194
[4]	刘宁宁,樊建席,林政宽. 基于地址空间的树型网络地址分配 Address Assignment Algorithm for Tree Network Based on Address Space 计算机科学, 2020, 47(2): 239-244. https://doi.org/10.11896/jsjkx.190400130
[5]	苏凡军,杜可怡. WSNs中基于信任度的节能机会路由算法 Trust Based Energy Efficient Opportunistic Routing Algorithm in Wireless Sensor Networks 计算机科学, 2020, 47(2): 300-305. https://doi.org/10.11896/jsjkx.190100172
[6]	周文祥, 乔学工. 基于能量优化的无线传感器网络任播路由算法 Anycast Routing Algorithm for Wireless Sensor Networks Based on Energy Optimization 计算机科学, 2020, 47(12): 291-295. https://doi.org/10.11896/jsjkx.190900069
[7]	李正阳, 陶洋, 周远林, 杨柳. 基于能量获取的能耗均衡多跳分簇路由协议 Energy-balanced Multi-hop Cluster Routing Protocol Based on Energy Harvesting 计算机科学, 2020, 47(11A): 296-302. https://doi.org/10.11896/jsjkx.200300002
[8]	侯明星,亓慧,黄斌科. 基于分布式压缩感知的无线传感器网络异常数据处理 Data Abnormality Processing in Wireless Sensor Networks Based on Distributed Compressed Sensing 计算机科学, 2020, 47(1): 276-280. https://doi.org/10.11896/jsjkx.180901667
[9]	王改云, 王磊杨, 路皓翔. 基于混合群智能算法优化的RSSI质心定位算法 RSSI-based Centroid Localization Algorithm Optimized by Hybrid Swarm Intelligence Algorithm 计算机科学, 2019, 46(9): 125-129. https://doi.org/10.11896/j.issn.1002-137X.2019.09.017
[10]	刘静, 赖英旭, 杨胜志, Lina Xu. 一种面向WSN的双向身份认证协议及串空间模型 Bilateral Authentication Protocol for WSN and Certification by Strand Space Model 计算机科学, 2019, 46(9): 169-175. https://doi.org/10.11896/j.issn.1002-137X.2019.09.024
[11]	王静, 仇晓鹤. 基于分簇和融合补偿策略的多维标度定位算法 Advanced MDS-MAP Localization Algorithm with Clustering and Fusion Compensation Strategy 计算机科学, 2019, 46(8): 145-151. https://doi.org/10.11896/j.issn.1002-137X.2019.08.024
[12]	叶娟, 陈元琰, 王明, 尼迎波. 多通信半径与角度修正的凸规划改进定位算法 Optimized Convex Localization Algorithm Using Multiple Communication Radius and Angle Correction 计算机科学, 2019, 46(6A): 317-320.
[13]	梁平元, 李杰, 彭娇, 王会. 基于协作MIMO的UWSN三维动态分簇路由算法研究 Research on 3D Dynamic Clustering Routing Algorithm Based on Cooperative MIMO for UWSN 计算机科学, 2019, 46(6A): 336-342.
[14]	李秀琴, 王天荆, 白光伟, 沈航. 基于压缩感知的两阶段多目标定位算法 Two-phase Multi-target Localization Algorithm Based on Compressed Sensing 计算机科学, 2019, 46(5): 50-56. https://doi.org/10.11896/j.issn.1002-137X.2019.05.007
[15]	孙博文, 韦素媛. 基于自适应调整策略灰狼算法的DV-Hop定位算法 DV-Hop Localization Algorithm Based on Grey Wolf Optimization Algorithm with Adaptive Adjutment Strategy 计算机科学, 2019, 46(5): 77-82. https://doi.org/10.11896/j.issn.1002-137X.2019.05.012

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed