摘要
在无线传感器网络的各种应用中,都需要知道传感器节点的相对或实际位置,所以实现传感器节点的定位是一项非常重要的任务.基于多维标度技术,提出了一种新的迭代分布式加权定位算法.通过对多维标度技术原理和分布式加权多维标度算法的分析,提出了新的局部成本函数和权值函数,从而得到一个模糊加权局部成本函数;得到每个传感器与其全部相邻节点的位置测量值和初始位置的估计值;最后通过最小化其相应的局部成本函数得到每个传感器的位置估计更新方程.仿真结果表明,提出的定位算法不仅能够减小定位误差,而且还可以降低收敛时间.
In various applications of wireless sensor network, it is necessary to know the relative or the actual position for the sensor nodes, so it is a very important task to complete the localization of sensor nodes.In this paper, a new iterative distributed weighted localization algorithm based on multidimensional scaling technique is proposed.In this way, a new local cost function and weight function is proposed through the analysis of multidimensional scaling technique and distributed weighted multidimensional scaling algorithm, thus a weighted local cost function is obtained.After the position measurements of each sensor from its total neighboring nodes and the estimations of its initial position is achieved, the position estimation update equation for each sensor is obtained by minimizing the corresponding local cost function.Simulation results show that the proposed algorithm can not only reduce the positioning error, but also reduce the convergence time.
作者
赵海军
夏金红
贺春林
ZHAO Hai-jun;XIA Jin-hong;HE Chun-lin(School of Computer, China-West Normal University, Nanchong 637009, Chin)
出处
《云南大学学报（自然科学版）》
CAS
CSCD
北大核心
2018年第4期645-651,共7页
Journal of Yunnan University(Natural Sciences Edition)
基金
国家自然科学基金(61379019)
西华师范大学基本科研业务费专项基金(14C002)
南充市科技支撑项目(15A0068)
关键词
无线传感器网络
多维标度
局部成本函数
定位误差
收敛时间
wireless sensor network
multidimensional scaling
local cost function
positioning error
convergence time
