45 / 2023-03-30 14:40:11
An GNSS/UWB based Robust Emergency Seamless Positioning Model for Indoor Environments
Emergency Positioning,GNSS/UWB,Robust EKF,Indoor and outdoor,seamless positioning
摘要待审
Houzeng Han / Beijing University of Civil Engineering and Architecture
Jian Wang / Beijing University of Civil Engineering and Architecture
Fei Liu / Beijing University of Civil Engineering and Architecture
In this paper, a new emergency positioning technique is proposed based on ad hoc GNSS/UWB (Global Navigation Satellite System/Ultra Wideband) network. The main innovations of the program are reflected in two aspects. First of all, a unified coordinate frame for indoor and outdoor environments is constructed dynamically with GNSS/UWB integration. In the outdoor environments, the high accuracy positioning can be achieved with GNSS/UWB equipment. The high accuracy indoor coordinate is obtained by measuring the range observations between adjacent network nodes and outdoor GNSS/UWB nodes, and the range information of the UWB network is transmitted to the cloud server center, a network adjustment algorithm is proposed to improve the positioning accuracy of the UWB network. Secondly, a UWB indoor location algorithm based on robust EKF (Extended Kalman Filter) is proposed. By analyzing the transfer characteristics of gross error in EKF model, a new robust EKF model is established. The model is constructed based on the statistical characteristics of redundant observation components and prediction residual. The robust equivalent gain matrix is constructed, and the robust positioning solution of UWB is obtained with iteration. The global test is carried out first to further improve the real-time operation efficiency. Finally, a field indoor and outdoor seamless positioning experiment was carried out to verify the effectiveness of the proposed algorithm. The results show that the positioning accuracy of UWB emergency network nodes can reach 0.35m. By applying the improved robust EKF positioning algorithm, the positioning accuracy can reach 0.38m, which is improved by 20.83% and 73.43% compared with standard EKF and least square method, respectively.
重要日期
  • 会议日期

    10月26日

    2023

    10月29日

    2023

  • 10月15日 2023

    摘要截稿日期

  • 10月15日 2023

    初稿截稿日期

  • 11月13日 2023

    注册截止日期

主办单位
国际矿山测量协会
中国煤炭学会
中国测绘学会
承办单位
中国矿业大学
中国煤炭科工集团有限公司
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