基于RSSI测距和免疫遗传算法的定位系统设计  

Design of Location System Based on RSSI Ranging and Immune Gene Algorism

作　　者：史兴燕[1,2] 韩敏[3] 

机构地区：[1]河南农业职业学院,河南中牟451450 [2]郑州大学,郑州450052 [3]河南职业技术学院,郑州450046

出　　处：《计算机测量与控制》2014年第1期194-196,共3页Computer Measurement &Control

基　　金：河南省教育厅自然科学研究计划项目(2011C520019);河南省软科学研究计划项目(132400410687)

摘　　要：为了提高基于物联网应用系统的节点定位精度,提出了一种基于RSSI测距和免疫遗传算法的定位系统;首先采用CC2431作为未知节点的主控制器,利用其所含的定位引擎获得参考锚节点的坐标值,并初始化参数路径损耗值PL(d0)、路径损失系数ρ和平均信号强度值RSSI,然后通过三边测量法获得节点的估算坐标,最后以最小化节点定位误差率为亲和度函数采用免疫遗传算法对参数进行优化,通过选择、交叉和变异操作对抗体进行不断进化,对相似抗体进行抑制以提高算法的全局寻优能力,并获得最终的定位模型;仿真实验表明:文中方法平均总定位误差为42.18%,能较为精确地定位节点,与其它方法相比,具有定位误差小的优点,具有很强的可行性。In order to improve the node positioning accuracy based on Internet of things, a location system based on RSSI ranging and immune gene system was proposed. Firstly, the CC2431 is used as the main controller of the unknown node and its position engine can obtain the coordinate value of the reference anchor node, the path loss value PL （d0） , the path loss coefficient p and the average signal intensity val ue RSSI , then the coordinate of the unknown node can be estimated through trilateration, finally, the immune gene algorism was used to op- timize the parameters using minimizing the node location error as the fitness function. The antibody was evolving through selection, crossover and mutation operation, the similar antibody was inhibited to improve the optimization ability of the algorism. The simulation results show that： the proposed method is accurate in node positioning, compared with other methods, has the advantages of small positioning error. So it is proved as strong feasibility.

关 键 词：RSSI测距 节点定位 免疫遗传 优化 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]