蚁群循环定位算法在WSNs节点定位中的应用

doi:10.3969/j.issn.1000-1158.2015.04.07

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Abstract To overcome the problems of complex algorithm, less accurate in the wireless sensor networks (WSNs) ranging and locating, the loop localization algorithm is proposed based on ant colony algorithm. Firstly, the experimental data is measured by the received signal strength indication (RSSI) method, and the signal attenuation model is established to calculate the distance formula. Secondly, the cycle localization algorithm is used to locate the eight anchor nodes cyclically and the average of the eight results as the best position of the blind node. Finally, the algorithm proposed is compared with the weighted centroid localization algorithm and three sided measurement, and the experimental results show that the cycle localization algorithm has higher positioning accuracy and stability.

Key words： Metrology Node location Wireless sensor networks RSSI Ant colony loop localization algorithm

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	Articles by authors
	ZHANG Li-guo
	REN Li-bin
	JIN Mei
	LI Pan
	ZHANG Zhi-fu

Cite this article:

ZHANG Li-guo,REN Li-bin,JIN Mei, et al. The Application of Ant Colony Loop Localization Algorithm in the WSNs Node Localization[J]. Acta Metrologica Sinica, 2015, 36(4): 365-369.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2015.04.07 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2015/V36/I4/365

［1］Kang J, Kim D, Kim J. RSS Self-calibration Protocol for WSN Localization ［C］ //International Symposium on Wireless Pervasive Computing, Daejeon, 2007:181-184.
［2］Gopakumar A, Jacob L. Localization in Wireless Sensor Networks using Particle Swarm Optimization［C］// IET Conference on Wireless, Mobile and Multimedia Networks, India, 2008:227-230.
［3］Zhang Z X, Cui H Q. Localization in 3D Sensor Networks Using Stochastic Particle Swarm Optimization［J］.Wuhan University Journal of Natural Sciences, 2012,17(6):544-548.
［4］Patil S, Zaveri M. MDS and Trilateration Based Localization in Wireless Sensor Network［J］.Wireless Sensor Network, 2011,(3):198-208.
［5］梁美玉,李莉,陈坤. 基于蚁群算法的井下无线传感网络节点定位研究［J］. 煤矿机械,2010,31(12): 48-50.
［6］Dalce R, Val T, Bossche A. Comparison of Indoor Localization Systems Based on Wireless Communications［J］.Wireless Engineering and Technology, 2011, (2):240-256.
［7］Zhu X Y, Feng Y. RSSI-based Algorithm for Indoor Localization ［J］.Communications and Network,2013, (5):37-42.
［8］冯晨,张玲华. 改进混合蛙跳算法在无线传感网定位中的应用［J］. 计量学报,2013, 34(4): 360-365.
［9］陈维克,李文峰,首珩,袁冰. 基于RSSI的无线传感网络加权质心定位算法［J］. 武汉理工大学学报(交通科学与工程版), 2006, 30(2): 265-268.
［10］王新芳,张兵,冯友兵.基于粒子群优化的改进加权质心定位算法［J］.计算机工程, 2012, 38(1): 90-95.
［11］徐林,傅成华. 基于Zigbee的三边测量算法误差研究及改进［J］. 微型机与应用, 2012, 31(21): 68-70.
［12］詹杰,吴伶锡,唐志军. 无线传感网络RSSI测距方法与精度分析［J］. 电讯技术, 2010, 50(4): 83-87.
［13］周海洋,余剑. 无线传感网络中基于RSSI的测距研究［J］. 电子测量技术, 2014, 37(1): 89-91.
［14］Dorigo M, Maniezzo V. Distributed optimization by ant colonies.［C］ // Proceedings of the 1st European Conference on Artificial Life, Milano , 1991,134-142.
［15］段海滨,王道波,于秀芬. 蚁群算法的研究现状及其展望［J］. 中国工程科学, 2007, 9(2): 98-102.
［16］王瑛辉,石理碧,孙坚. 基于zigbee技术的无线传感网络在能源计量系统中的应用［J］. 计量技术, 2013, (11) : 30-32.