河北大学学报(自然科学版) ›› 2021, Vol. 41 ›› Issue (3): 329-336.DOI: 10.3969/j.issn.1000-1565.2021.03.016

• • 上一篇    

基于UWB的三维定位和优化滤波方法

李楠1,梁冰2   

  • 收稿日期:2020-06-20 发布日期:2021-05-28
  • 作者简介:李楠(1978—),男,河北三河人,华北科技学院讲师,主要从事机械电子工程方向研究.E-mail:linan78@ncist.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(61663014);中央高校基本科研业务费资助(3142020005)

3D positioning and optimal filtering method based on UWB

LI Nan1,LIANG Bing2   

  1. 1.Institute of Mechanical and Electrical Services, North China Institute of Science and Technology, Langfang 065201, China; 2.Institute of Electronic and Information Engineering, North China Institute of Science and Technology, Langfang 065201, China
  • Received:2020-06-20 Published:2021-05-28

摘要: 为了提高室内定位的精度,研究适用于室内定位的基于超宽带(UWB)的三维定位和优化滤波方法,建立基于UWB的三维定位模型;分析三维定位数据利用卡尔曼滤波、平滑滤波、中值滤波、曲线拟合4种算法,在所需时间、环境需求、性价比和精度方面的特性.实验结果表明:相比于平滑滤波、中值滤波、曲线拟合算法,卡尔曼滤波更适合在室内环境的三维定位要求.

关键词: 三维定位, 优化滤波, 超宽带, Python语言

Abstract: In order to improve the accuracy of indoor positioning, this paper studies the ultra wideband(UWB)based three-dimensional positioning and optimal filtering method suitable for indoor positioning. The three-dimensional positioning model is established based on UWB. The characteristics of three-dimensional positioning data is analyzed using Kalman filter, smoothing filter, median filter and curve fitting algorithm in terms of time required, environmental requirements, cost performance and accuracy. The experimental results show that. compared with smooth filter, median filter and curve fitting algorithm, Kalman filter is more suitable for 3D positioning in indoor environment.

Key words: 3D positioning, optimization filtering, ultra wide band, Python language

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