测绘通报 ›› 2023, Vol. 0 ›› Issue (9): 52-58.doi: 10.13474/j.cnki.11-2246.2023.0264

• 学术研究 • 上一篇    下一篇

PDR+BLE融合的室内实时定位方法

徐浩1, 吴雪2, 李春光1, 秘金钟3, 陈冲4, 李得海3   

  1. 1. 济南市房产测绘研究院, 山东 济南 250001;
    2. 山东皓宇资讯有限公司, 山东 济南 250101;
    3. 中国测绘科学研究院, 北京 100830;
    4. 中国电子科技集团第五十四研究所, 河北 石家庄 050081
  • 收稿日期:2022-12-13 发布日期:2023-10-08
  • 通讯作者: 李得海。E-mail:lidh@casm.ac.cn
  • 作者简介:徐浩(1994—),男,硕士,研究方向为卫星定位与导航技术。E-mail:xh0632@163.com
  • 基金资助:
    国家重点研发计划(2021YFB3900803);河北省自然资源厅科技项目(13000022P00EEC410090F);河北省技术创新引导计划项目科技冬奥专项(21477603D)

Indoor real-time fusion positioning based on PDR+BLE

XU Hao1, WU Xue2, LI Chunguang1, BEI Jinzhong3, CHEN Chong4, LI Dehai3   

  1. 1. Jinan Real Estate Measuring Institute, Jinan 250001, China;
    2. Shandong Haoyu Information Co., Ltd., Jinan 250101, China;
    3. Chinese Academic of Surveying and Mapping, Beijing 100830, China;
    4. The 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang 050081, China
  • Received:2022-12-13 Published:2023-10-08

摘要: 由于导航卫星信号在室内被遮挡,室内定位技术逐渐成为泛在导航定位领域的研究热点。行人航迹推算(PDR)和低功耗蓝牙(BLE)定位是惯性定位和射频信号定位的常用定位手段,PDR定位连续稳定但存在累积误差,BLE定位无误差累积但定位精度较差。为此,本文面向室内复杂环境行人自主定位需求,对PDR和BLE的实时融合定位展开了研究。首先针对PDR误差累积问题,提出了BLE临近校正PDR的改进算法;然后针对BLE定位粗差大的的问题,提出了基于扩展卡尔曼滤波(EKF)的自适应抗差PDR+BLE融合定位算法。试验结果表明,相比传统算法,BLE临近校正PDR算法定位精度提高了19%,基于EKF的自适应抗差融合定位精度提高了21%,定位精度和稳定性都有显著提升,在室内定位领域中具有较高的适用性和可扩展性。

关键词: 室内定位, PDR定位, BLE定位, EKF, 融合定位

Abstract: Indoor positioning technology is becoming a hot research topic in the field of ubiquitous navigation and positioning due to the blockage of navigation satellite signals indoors. PDR and BLE positioning are the common positioning means of inertial positioning and RF signal positioning, but PDR positioning is continuous and stable but has accumulated errors, while BLE positioning has no accumulated errors but has poor positioning accuracy. In this paper, PDR/BLE real-time fusion positioning is proposed to meet indoor positioning requirements in complex environments. Firstly, the improved algorithm of BLE proximity correction PDR is proposed for the problem of PDR error accumulation; then the adaptive robust PDR/BLE fusion positioning algorithm based on EKF is proposed for the problem of large coarse difference in BLE positioning.The results show that the BLE proximity correction PDR algorithm improves the localization accuracy by 19% and the EKF-based adaptive robust fusion positioning accuracy by 21% compared with the traditional algorithms, which have significant improvement in both positioning accuracy and stability.It will also have high applicability and scalability in the field of indoor positioning.

Key words: indoor positioning, PDR positioning, BLE positioning, extended Kalman filter, fusion positioning

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