《计算机应用研究》|Application Research of Computers

基于卡尔曼滤波的室内定位可信指纹库研究与实现

Research and implementation of trusted fingerprint library in indoor localization based on Kalman filter

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作者 吴蔚,谭献海,钱晓群,彭宏玉
机构 西南交通大学 信息科学与技术学院,成都 611756
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文章编号 1001-3695(2020)06-047-1835-04
DOI 10.19734/j.issn.1001-3695.2018.11.0906
摘要 在基于iBeacon技术的指纹库室内定位算法中,由于室内环境中人员走动、多径效应等因素所带来的噪声影响,需要加以抑制。卡尔曼滤波算法可以用来抑制这些噪声,进而建立可信(即更接近真实值)的指纹库。重点研究在使用卡尔曼滤波算法时,根据具体的室内环境进行测量,估算出不同iBeacon节点的观测噪声以及卡尔曼滤波算法的迭代初值,使卡尔曼滤波算法更快收敛。实验结果表明,通过卡尔曼滤波算法建立的指纹库比通过平均值建立的指纹库,定位精确度和稳定度均有明显的提升。
关键词 iBeacon; 室内定位; 卡尔曼滤波; 实时定位
基金项目 博创基金资助项目(1401801)
西南交大合作智慧水务项目(1200305)
唐山市室内定位重点实验室建设项目(220020502)
本文URL http://www.arocmag.com/article/01-2020-06-047.html
英文标题 Research and implementation of trusted fingerprint library in indoor localization based on Kalman filter
作者英文名 Wu Wei, Tan Xianhai, Qian Xiaoqun, Peng Hongyu
机构英文名 School of Information Science & Technology,Southwest Jiaotong University,Chengdu 611756,China
英文摘要 When using the fingerprint localization algorithm based on iBeacon technology, the noise influence caused by factors such as multipath effect and personnel disturbance needed to be suppressed. This paper used Kalman filtering algorithm to suppress these noises and establish a reliable(closer to the true value) fingerprint library. This paper's key points were the observation noise of different iBeacon nodes and the iterative initial value of the Kalman filter algorithm. According to these two values estimated by the measurement in the specific indoor environment, the Kalman filter algorithm converged faster. The experimental results show that the fingerprint database established by Kalman filter algorithm has a significant improvement in positioning accuracy and stability compared with the fingerprint database established by the average value.
英文关键词 iBeacon; indoor positioning; Kalman filtering; real-time positioning
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收稿日期 2018/11/26
修回日期 2019/1/11
页码 1835-1838
中图分类号 TP301.6
文献标志码 A