一种基于WiFi的位置指纹和PDR的缠绕融合定位方法  

A WiFi-based location fingerprinting and PDR winding fusion positioning method

作　　者：朱熙玄 华杭波 孔明 梁晓瑜 ZHU Xixuan;HUA Hangbo;KONG Ming;LIANG Xiaoyu(School of Metrology and Testing Engineering,China Jiliang University,Hangzhou 310018,China)

机构地区：[1]中国计量大学计量测试工程学院,浙江杭州310018

出　　处：《现代电子技术》2024年第11期150-155,共6页Modern Electronics Technique

基　　金：国家市场监督管理总局技术保障专项(2022YJ21);浙江省市场监督管理局科技计划(全额自筹)项目(ZC2023057)。

摘　　要：目前基于接收信号强度(RSSI)的位置指纹定位与行人航位推算(PDR)的组合定位算法,大多着重于PDR的步态解算优化,未考虑指纹定位的鲁棒性差和基础定位误差较大带来的负面影响,没有针对环境特性有效地将两种算法在流程上充分融合。文中提出一种基于WiFi-RSSI的位置指纹和PDR相结合的缠绕融合定位方法,根据平面楼层环境及各区域内行人运动程度规划实验范围,通过递进平均滤波校准PDR的结果,减小PDR的累计误差。其次结合环境划分递进位置指纹库,在对应的不同区域使用对应的离线指纹库,通过PDR解算步态数据校准位置指纹的异向偏移,输出最终指纹定位结果,减小了位置指纹法的定位偏差。最后通过无迹卡尔曼(UKF)择优观测输入进行融合滤波,得到最终结果。通过仿真实验验证,该算法效果相较于位置指纹法和PDR,定位精度提升了41%和29%,较现有的组合定位方法提升了28%。At present,the combined positioning algorithm based on received signal strength indication(RSSI)and pedestrian dead reckoning(PDR)mostly focuses on gait optimization of PDR.The negative effects of poor robustness of fingerprint positioning and large error of basic positioning are not taken into account.In addition,the two algorithms are not integrated effectively in the process according to the environmental characteristics.In this paper,a WiFi-RSSI based location fingerprinting winding fusion positioning method combining PDR is proposed.The experimental range is planned according to the floor environment and pedestrian movement degree in each area,and the PDR results are calibrated by progressive average filtering to reduce the cumulative error of PDR.According to the environment division of progressive location fingerprint database,the offline fingerprint databases are adopted in the corresponding different areas,and the gait data is solved by PDR to calibrate the location fingerprinting offset,output the final fingerprint location result,and reduce the positioning deviation of location fingerprinting method.Finally,the fusion filtering of optimal observation inputs is carried out by the unscented Kalman filter(UKF),and the final result is obtained.Simulation results show that the positioning accuracy of the proposed algorithm is improved by 41%and 29%,respectively,in comparison with that of location fingerprinting method and PDR,and by 28%in comparison with that of the existing combined positioning method.

关 键 词：室内定位 位置指纹法 行人航位推算 无迹卡尔曼滤波 融合定位 组合定位 

分 类 号：TN713-34[电子电信—电路与系统] TN92