迭代粒子群优化的水下无线传感器网络节点自定位算法  

A Localization Method for Underwater Wireless Sensor Networks Based on Modified Particle Swarm Optimization Algorithms

作　　者：常鲁杰[1,2] 刘明雍[1] 张立川[1] 孙永昭[1] 黄帅 Chang Lujie Liu Mingyong Zhang Lichuan Sun Yongzhao Huang Shuai(School of Marine Science and Techology, Northwestern Polytechnical University, Xi＇an 710072, China 96617 Unit PLA,Luzhou 646000, China Xi＇an Aerosspace Precision Mechatronric Institute, Xi＇an 710072, China)

机构地区：[1]西北工业大学航海学院 [2]96617部队 [3]西安航天精密机电研究所

出　　处：《西北工业大学学报》2017年第4期648-654,共7页Journal of Northwestern Polytechnical University

基　　金：国家自然科学基金(51179156;51379176;51679201)资助

摘　　要：传统MDS-MAP(multi-dimensional scaling MAP)算法使用节点间的最短路径作为真实距离计算节点位置,但当水下无线传感器网络(underwater wireless sensor networks,UWSN)构型非均匀时,最短路径将严重偏离节点间真实距离,位置计算将产生较大误差。针对此不足,文中设计了一种基于迭代粒子群优化的RQ-PSO定位算法。该方法利用MDS-MAP算法对传感器节点完成粗定位,引入几何约束来限制粒子群初始种群范围,并采用鲁棒四边形规则对未知节点位置进行优化求解。通过理论分析和仿真,结果表明,该算法收敛速度明显高于传统粒子群算法(PSO),定位精度高于传统MDSMAP与PSO算法,且RQ-PSO算法具有较强的鲁棒性。For the problem that the localization error of the traditional Multi-dimensional Scaling MAP （MDS- MAP） algorithm is oversensitive to the distance matrix between nodes in Underwater Wireless Sensor Network （UWSN）, a robust quadrilateral based modified Particle Swarm Optimization （RQ-PSO） is proposed. Inspired by the robust quadrilateral, geometrical constraint is introduced to narrow down the range of the initial particle swarm after the rough localization by applying MDS-MAP algorithm. The experiment results show that the proposed algo- rithm can decrease the location error, improve accuracy and the rate of convergence with strong robustness, com- pared with MDS-MAP and classical PSO.

关 键 词：水下传感器网络 节点定位 MDS—MAP算法 改进粒子群优化 

分 类 号：TP212.1[自动化与计算机技术—检测技术与自动化装置]