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J4  2014, Vol. 48 Issue (1): 100-104    DOI: 10.3785/j.issn.1008-973X.2014.01.015
计算机技术﹑电信技术     
WSN定位中的RSSI概率质心计算方法
程森林,李雷,朱保卫,柴毅
重庆大学 自动化学院,重庆 400044
Computing method of RSSI probability centroid for location in WSN
CHENG Sen-lin, LI Lei, ZHU Bao-wei, CHAI Yi
College of Automation, Chongqing University, Chongqing 400044, China
 全文: PDF(704 KB)  
摘要:

 针对最小二乘综合定位精度不高与极大似然估计定位计算量大的问题,提出基于接收信号强度指示(RSSI)模型概率质心的定位方法.该方法采用在一定显著度下的锚节点定位环重叠区域代替整个无线传感网络(WSN)的分布区域,以重叠区域概率密度质心作为未知节点位置的估计.通过实验仿真获得2种方法在锚节点标准差存在差异时的定位误差曲线,对比结果显示,该方法的定位精度高于最小二乘定位方法,验证了该算法优于最小二乘定位算法.研究表明,该方法具有与极大似然估计相同数量级的定位精度,但计算量减少95%~97.5%.

关键词: 无线传感网络(WSN)定位方法重叠区域RSSI概率质心    
Abstract:

A probability-centroid locating method based on RSSI was presented aiming at the low comprehensive locating precision in the least square locating method and large computing amount in maximum likelihood estimation locating. The algorithm adopted the overlapping area, which should be locating ring of anchor node under a certain outstanding degree, replacing the whole distribution area in wireless sensor network (WSN). Then the probability-density-centroid of overlapping area was figured out as the estimated value of unknown node. Locating error curves of the two methods were obtained under the existing differences of standard deviation of anchor nodes. The comparative results demonstrated that the locating precision of the method was higher than that of least square locating method, which validated that the algorithm would excel the least square locating algorithm. Results show that the method is provided with the same locating precision as maximum likelihood estimation, and the computing amount is reduced by 95%~97.5%.

Key words: wireless sensor network (WSN)    locating method    overlapping area    RSSI    probability-centroid
出版日期: 2014-02-21
:  TP 273  
基金资助:

国家自然科学基金资助项目(60974090).

作者简介: 程森林(1968-),男,副教授,从事检测技 术与自动化系统、GPRS与GPS等遥测遥控技术、模式识别与图像技术、计算机层析成像技术与系统研究. E-mail:csl@cqu.edu.cn
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引用本文:

程森林,李雷,朱保卫,柴毅. WSN定位中的RSSI概率质心计算方法[J]. J4, 2014, 48(1): 100-104.

CHENG Sen-lin, LI Lei, ZHU Bao-wei, CHAI Yi. Computing method of RSSI probability centroid for location in WSN. J4, 2014, 48(1): 100-104.

链接本文:

http://www.zjujournals.com/xueshu/eng/CN/10.3785/j.issn.1008-973X.2014.01.015        http://www.zjujournals.com/xueshu/eng/CN/Y2014/V48/I1/100

[1] ZHU Yuan-chen, GORTLER S J, THURSTON D. Sensor network localization using sensor perturbation [J]. ACM Transactions on sensor Networks, 2011, 7(4): 123.
[2] PAPAMANTHOU C, PREPARATA F P, TAMASSIA R. Algorithms for location estimation based on RSSI sampling [C]∥4th International Workshop on Algorithmic Aspects of Wireless Sensor Networks. Reykjavik: Springer, 2008: 72-86.
[3] GRACIOLI G, FROHLICH A A, PIRES R P, et al. Evaluation of an RSSI-based location algorithm for wireless sensor networks [J]. IEEE Latin America Transactions, 2011, 9(1): 830-835.
[4] NARZULLAEV A, PARK Y, KOOKEYEOL Y, et al. A fast and accurate calibration algorithm for real-time locating systems based on the received signal strength indication [J]. International Journal of Electronics and Communications, 2010, 65(4): 305-311.
[5] WANG Xin-wei, YUAN Shao-ping, LAUR R. Dynamic localization based on spatial reasoning with RSSI in wireless sensor networks for transport logistics [J]. Sensor and Actuators A: Physical, 2011, 171(2): 421-428.
[6] ZHANG Rong-biao, GUO Jian-guang, CHU Fu-huan, et al. Environmental adaptive indoor radio path loss model for wireless sensor networks localization [J]. International Journal of Electronics and Communications, 2011, 65(12): 1023-1031.
[7] 田孝华,周义建. 无线电定位理论与技术[M]. 北京:国防工业出版社,2011.
[8] 王建刚,王福豹,段渭军.加权最小二乘估计在无线传感器网络定位中的应用[J].计算机应用研究,2006,10(1):1-3.
WANG Jian-gang, WANG Fu-bao, DUAN Wei-jun. Application of weighted least square estimates on wireless sensor network node location [J]. Application Research of Computers, 2006, 10(1): 1-3.
[9] MIYAUCHI K, OKAMOTO E, IWANAMI Y. Performance improvement of location estimation using deviation on received signal in wireless sensor networks [C]∥2010 2nd International Conference on Ubiquitous and Future Networks. Korea: IEEE, 2010: 66-70.
[10] NANDA M, KUMAR A, KUMAR S. Localization of 3D WSN using Mamdani Sugano fuzzy weighted centriod approaches [C]∥2012 IEEE Students’ Conference on Electrical, Electronics and Computer Science. Bhopal: IEEE, 2012:15.
[11] TIE Qiu, YU Zhou, FENG Xia. A localization strategy based on n-times trilateral centriod with weight [J]. International Journal of Communication Systems, 2012, 25(1): 351-357.
[12] VELIMIROVIC A, DJORDJEVIC G L, VELIMIROVIC M M, et al. Fuzzy ring-overlapping range free localization method for wireless sensor networks [J]. Computer Communications, 2012, 35(13):1590-1600.
[13] LU Ke-zhong, XIANG Xiao-hua, ZHANG Dian, et al. Localization algorithm based on maximum a posteriori in wireless sensor networks [J]. International Journal of Distributed Sensor Networks, 2012: 260-302.

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