摘要
信号指纹数据库(radio fingerprint database, RFDB)是基于WLAN的室内定位最重要的条件支撑。提出一种RFDB的测绘方法,该方法不依赖于额外的硬件或室内地图信息,通过图优化的方法融合手机的惯性数据、信号指纹数据,从而获得最大似然的室内位置估计,并根据位置的估计结果获得室内的RFDB,可用于WLAN室内定位。通过实验对比,证明了所提出的方法相比于地图点按方法定位误差下降了1.0 m,相比于基于高斯过程插值的方法在参考点稀疏的环境下定位误差下降了0.8 m。
Radio fingerprint databased(RFDB) is the prerequisite for WLAN based indoor positioning of the utmost importance. In this paper, a RFDB surveying method is proposed without dependence on additional information such as external hardware or indoor maps. In the method, the inertial data and the fingerprinting data are fused through graph optimization(GO). Then the indoor positions along with the RFDB can be estimated with greatest consistency of all types of information. The acquired RFDB can then be adopted for WLAN based indoor positioning. Experiments are carried out to evaluate the proposed method. It is proved that compared with pin point method, the proposed method has a mean positioning error decrease of about 1.0 m and compared with the Gaussian process based method with sparse reference points, the number is 0.8 m.
作者
李竞
卢建洲
Li Jing;Lu Jianzhou(Henan Agricultural Vocational College,Zhengzhou 451450,China;ZhengZhou University of Light Industry,Zhengzhou 450002,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2020年第2期29-35,共7页
Journal of Electronic Measurement and Instrumentation
基金
国家自然基金重点项目(51534002)
“十三五”国家重点研发计划(2017YFC0804103)资助项目。
关键词
WLAN定位
信号指纹数据库
图优化
WLAN based indoor positioning
radio fingerprint database
graph optimization
