基于改进麻雀搜索算法优化的RSSI定位  

RSSI localization based on improved sparrow search algorithm optimization

作　　者：刘博 李卓 刘伟[1,2] 韦嘉恒[1] LIU Bo;LI Zhuo;LIU Wei;WEI Jiaheng(College of Information Science and Engineering,Guilin University of Technology,Guilin 541004,China;Guangxi Key Laboratory of Embedded Technology and Intelligent System,Guilin University of Technology,Guilin 541004,China)

机构地区：[1]桂林理工大学信息科学与工程学院,广西桂林541004 [2]广西嵌入式技术与智能系统重点实验室桂林理工大学,广西桂林541004

出　　处：《传感器与微系统》2024年第9期127-130,共4页Transducer and Microsystem Technologies

摘　　要：针对传统接收信号强度指示(RSSI)测距受环境中不同因素干扰,导致定位精度不高的问题,提出基于改进麻雀搜索算法(ISSA)优化的RSSI定位算法。首先,通过混合滤波对RSSI值优化处理,剔除异常值并消除波动,RSSI测距模型将滤波后可靠的信号值换算为距离。其次,对基础麻雀搜索算法(SSA)进行改进,得到未知节点的精确坐标。实验结果表明:与另一种ISSA及粒子群优化万有引力搜索算法(PSOGSA)混合定位算法相比,该算法具有更高的定位精度。Aiming at the problem that traditional received signal strength indication(RSSI)ranging is interfered by different factors in environment,resulting in low positioning precision,a RSSI localization algorithm based on improved sparrow search algorithm(ISSA)is proposed.Firstly,the RSSI value is optimized and processed by hybrid filtering to eliminate outliers and fluctuations.The RSSI ranging model converts the filtered reliable signal value into distance.Secondly,the basic sparrow search algorithm(SSA)is improved,and the precise coordinates of the unknown nodes are obtained by multiple cyclic iterations.Experimental results show that compared with another ISSA and particle swarm optimization gravitation search algorithm(PSOGSA),this algorithm has higher localization precision.

关 键 词：无线传感器网络 接收信号强度指示 混合滤波 麻雀搜索算法 节点定位 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]