摘要
为解决室内WiFi定位精度较低及行人航位推算(PDR)定位存在累积误差的问题,提出一种基于扩展Kalman滤波(EKF)的WiFi-PDR融合定位算法。WiFi通过改进的WKNN算法实现匹配定位,根据定位点与K近邻点的接收信号强度指示相对偏差进行权值修正,PDR定位采用多重约束条件的步态检测和在线步长估计方法。在此基础上,将EKF作为WiFi和PDR定位的融合滤波器,以降低WiFi定位回跳和PDR累计误差,从而提高定位精度。实验结果表明,在多次行迹转弯条件下,该融合定位算法的定位精度可达1.8 m。
Indoor WiFi location accuracy is low,and Pedestrian Dead Reckoning(PDR) location has the problem of cumulative error.Therefore,a WiFi-PDR fusion location algorithm based on Extended Kalman Filter(EKF) is proposed.WiFi achieves matching location by improved WKNN algorithm,and the relative deviation of the Received Signal Strength Indication(RSSI) between the location point and the K-nearest neighbor point is used for weight correction.PDR location adopts gait detection with multiple constraints and online step size estimation.On this basis,EKF is used as the fusion filter of WiFi and PDR location to reduce the WiFi location bounce and the cumulative error of PDR to improve the location accuracy.Experimental results show that the location accuracy of the fusion algorithm can reach 1.8 m under the condition of multiple traveling turns.
作者
刘庆
关维国
李顺康
王芳
LIU Qing;GUAN Weiguo;LI Shunkang;WANG Fang(College of Electronic and Information Engineering,Liaoning University of Technology,Jinzhou,Liaoning 121001,China;State Grid Liaoning Electric Power Limited Company Jinzhou Power Supply Company,Jinzhou,Liaoning 121000,China)
出处
《计算机工程》
CAS
CSCD
北大核心
2019年第4期66-71,77,共7页
Computer Engineering
基金
辽宁省自然科学基金"基于北斗与泛在无线网络的室内外协同定位技术研究"(20170540437)
辽宁省教育厅重大科技平台科技项目(JP2016015)
