距离修正的混沌粒子群多维标度定位算法
Multidimensional scaling localization algorithm based on matrix correction and chaotic particle swarm optimization
作者：齐小刚(西安电子科技大学数学与统计学院)；刘兴成(西安电子科技大学数学与统计学院)；刘立芳(西安电子科技大学计算机学院)；王振宇(西安电子科技大学数学与统计学院)；张权(西安电子科技大学数学与统计学院)
Author：QI Xiao-Ggang(School of Mathematics and Statistics, Xidian University)；LIU Xing-Cheng(School of Mathematics and Statistics, Xidian University)；LIU Li-Fang(School of Computer Science and Technology, Xidian Liniversity)；WANG Zhen-Yu(School of Mathematics and Statistics, Xidian University)；ZHANG Quan(School of Mathematics and Statistics, Xidian University)
收稿日期：2017-06-01 年卷（期）页码：2018,55(3):483-488
期刊名称：四川大学学报: 自然科学版
Journal Name：Journal of Sichuan University (Natural Science Edition)
关键字：无线传感器网络；多维标度定位；网络空洞；距离修正；混沌粒子群算法
Key words：Wireless sensor network; Multidimensional scaling localization; Network hole; Distance correction; Chaotic particle swarm optimization algorithm
基金项目：国家自然科学基金 (61572435, 61472305)； 陕西省自然科学基金（2015JZ002, 2015JM6311）； 浙江省自然科学基金LZ16F020001）； 宁波市自然科学基金（2016A610035）； 空间测控通信创新探索基金（KJCK1608）
中文摘要
针对不规则网络以及网络空洞造成估计距离与欧氏距离相差较大,导致定位精度不足这一问题,提出一种距离修正的混沌粒子群多维标度定位算法(CMDS-CPSO).首先通过递推策略计算节点对距离,利用接收信号强度对距离加权修正,以减少距离误差,回避网络空洞问题.然后采用混沌粒子群算法对坐标转化参数问题进行优化,进一步降低坐标转换中参数所带来的影响.通过对比SPSO-MDS算法与MDS-DMC算法,仿真结果表明,距离修正的混沌粒子群算法能够明显改善节点定位精度,具有更好的鲁棒性和对不规则网络的适应性.
英文摘要
Against the problem of a great distance between estimated distance and actual Euclidean distance caused by irregular network and network hole that eventually results in insufficient localization accuracy, an improved multidimensional scaling localization algorithm based on matrix correction and chaotic particle swarm optimization(CMDS-CPSO) is proposed. Distance among each pair of nodes is calculated by recursive strategy and further weighted by the received signal strength, so as to reduce the distance error between estimated distance and actual Euclidean distance as well as avoid the problem of network hole. Then chaotic particle swarm optimization is adopted to solve the parameter problem during the coordinate conversion process, which could loosen the influence of parameters to a high degree. Compared with the SPSO-MDS algorithm and MDS-DMC algorithm, the simulations reveal that the proposed algorithm of CMDS-CPSO could not only significantly improve the localization accuracy of nodes but has better robustness and adaptability to irregular networks.
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