摘要
针对基于RSSI的无线传感器网络室内移动目标定位算法易受干扰、波动较大等问题,提出一种改进的RSSI多维标度室内定位算法(RSSI-CMDS),采用节点信号强度建立相异性矩阵,多维标度法求解节点相对坐标,根据参考节点的实际坐标,通过平面四参数模型进行坐标转换,运用粒子群算法优化参数,计算移动节点的实际坐标(移动节点真实位置)。仿真和实验表明,算法抗RSSI扰动性强,定位精度高,能够满足室内定位跟踪及低成本定位系统的需求。
Aiming at the problems that the indoor mobile object localization algorithms for wireless sensor networks （WSNs） based on RSSI methods are easy to be interfered and the localization errors have large variation, a novel im- proved algorithm called RSSI-CMDS （received signal strength indicator and classic multidimensional scaling）is pro- posed. The RSSIs of the nodes in WSNs are used to construct the dissimilarity matrix. The classical MDS method is used to solve the relative coordinates of the nodes and perform the coordinate transform with planar four parameter model according to the actual coordinates of the reference nodes. The particle swarm optimization （PSO） algorithm is used to optimize the parameters, and then the actual coordinates （ the real positions） of the mobile nodes are calculat- ed. Simulations and experiment results show that the proposed RSSI-CMDS algorithm has good positioning perform- ance even in the presence of random RSS fluctuations due to multi-path fading and shadowing, can meet the require- ments of indoor localization tracking and low-cost localization system.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2014年第2期261-268,共8页
Chinese Journal of Scientific Instrument
基金
国家工信部2011年物联网发展专项资金
国家科技重大专项(2011BAJ03B13)
重庆市科技攻关项目(cstc2012gg-yyjs40008)资助
关键词
无线传感器网络
室内定位
多维标度法
接收信号强度指示
粒子群算法
wireless sensor networks （WSNs）
indoor localization
multidimensional scaling （ MDS ）
received signal strength indication （RSSI）
particle swarm optimization （ PSO ）
