无线传感器网络煤矿井下RSSI自适应定位算法  

Adaptive localization algorithm for WSNs used in coalmine underground based on RSSI

作　　者：曹开来 余敏[1] 

机构地区：[1]江西师范大学计算机信息工程学院,江西南昌330022

出　　处：《传感器与微系统》2014年第6期129-132,共4页Transducer and Microsystem Technologies

基　　金：国家自然科学基金资助项目(41164001);国际科技合作专项资助项目(35-14)

摘　　要：通过对无线信号传播模型进行有效分析，发现路径衰减指数取值的固定性是导致测距误差的主要原因之一。在传统接收信号强度指示（RSSI）定位算法基础上，结合煤矿井下巷道环境特征，提出一种自适应RSSI三角质心定位算法，算法通过动态计算信标节点到盲节点的路径损耗指数，从而提高了测距算法对环境的适应性，算法结合巷道环境特征和信标节点到盲节点的距离公式，对两圆相交的情况进行讨论，最终计算出盲节点的有效坐标。仿真实验表明：巷道宽度在一定范围内（5—15m），定位误差平均值均小于0．5m，定位误差小于1m的概率均高达90％以上，具有较高的定位精度。Through effective analysis on wireless signal propagation model, it is found that fixity of path attenuation index values is one of the main reasons which causes ranging error. Based on traditional received signal strength indicator（RSSI） location algorithm, combine coal mine roadway environmental characteristics, propose a self-adaptived RSSI triangle centroid localization （SRTCL） algorithm, through dynamically calculating the path attenuation index between the beacon nodes and blind node, thereby increase adaptability of ranging algorithm on environment, and the algorithm combines with coal mine roadway environment characteristics and distance formula of beacon node to the blind node, discuss final calculate effective coordinate of blind node. Simulation results show that aisle width at range of 5 - 15 m of two circles, the averaged positioning errors are less than 0.5 m, the probability of positioning error which is less than lm are above 90 % ,it has high positioning precision.

关 键 词：信号传输模型 路径衰减指数 盲节点 煤矿井下巷道 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]