一种基于WiFi指纹特征匹配的加权K近邻室内定位算法

摘要

Because of the fluctuation of WiFi signal intensity,which leads to the low precision of the location fingerprint sys-tem,a weighted K nearest neighbor indoor localization algorithm is improved.The characteristics of the received signal strength are analyzed by the interval between the fingerprint sampling and the number of WiFi access points.And the finger-print database is optimized to achieve positioning.The influence of the number of access points,sampling interval and K val-ue on the positioning accuracy is analyzed.The experimental results show that the algorithm can achieve 1.98 m positioning accuracy.%针对WiFi信号强度测量存在波动,位置指纹定位系统精度低的问题,提出了一种改进的加权K近邻室内定位算法.从指纹采样间隔、WiFi接入点的数量等方面分析接收信号强度特性,优化指纹数据库,实现室内定位,并分析了接入点数量、采样间隔、K取值对定位精度的影响.实验结果表明,利用该算法可以实现1.98 m的定位精度.