CAJ | 학술논문

为提高煤矿井下传感器网络节点定位的实时性，提出了一种基于接收信号强度( RSSI )的快速定位算法。该算法在井下巷道锚节点双链式部署结构的基础上，运用高斯密度函数对节点接收到的锚节点信号强度最大的RSSI信号进行滤波处理，再应用指数因子和滤波后RSSI值直接计算确定未知节点的坐标。指数因子采用一种改进的量子粒子群优化算法及定位均方根误差最小的准则进行优化。所提出的算法具有定位速度快、计算量小的优点，仿真实验结果验证了算法的可行性与有效性，适用于煤矿井下无线传感器网络实时定位系统中。
위제고매광정하전감기망락절점정위적실시성，제출료일충기우접수신호강도( RSSI )적쾌속정위산법。해산법재정하항도묘절점쌍련식부서결구적기출상，운용고사밀도함수대절점접수도적묘절점신호강도최대적RSSI신호진행려파처리，재응용지수인자화려파후RSSI치직접계산학정미지절점적좌표。지수인자채용일충개진적양자입자군우화산법급정위균방근오차최소적준칙진행우화。소제출적산법구유정위속도쾌、계산량소적우점，방진실험결과험증료산법적가행성여유효성，괄용우매광정하무선전감기망락실시정위계통중。
To improve the realtime performance of node localizationin in coal-mine underground wireless sensor networks, a fast node localization algorithm based on RSSI is proposed. On the base of the double-chain deployment structure of anchor nodes in coal-mine underground,the largest RSSI signals received from the anchor nodes are processed by the filter with Gauss density function,and the coordinates of the unknown nodes are calculated directly by the filtered RSSI signals and exponential factors. The exponential factors are optimized by an improved quantum-behaved particle swarm optimization algorithm and the criterion of the root mean square error minimum. The algorithm proposed has the advantage of fast positioning speed and low computational complexity and the simulation results verify the feasibility and effectiveness of the algorithm,which can be suitable for real time positioning system in coal mine underground wireless sensor networks.