Bulletin of Surveying and Mapping ›› 2024, Vol. 0 ›› Issue (7): 24-29.doi: 10.13474/j.cnki.11-2246.2024.0705

Previous Articles     Next Articles

Combined GNSS+5G positioning based on adaptive optimal selection-anti-differential adaptive Kalman filter hybrid model

HU Xiangxiang1, SONG Bao2,3, SHI Yaya1,4, PANG Dongdong1, WU Chengyong1, ZHANG Lili1, LI Yifei1   

  1. 1. School of Resource and Environmental Engineering, Tianshui Normal University, Tianshui 741001, China;
    2. School of Automation, Beijing Institute of Technology, Beijing 100081, China;
    3. Wuxi Research Institute of Nanjing University of Information Engineering, Wuxi 214000, China;
    4. Northwest Institute of Eco-Environment and Resources, CA, Lanzhou 730000, China
  • Received:2023-10-07 Published:2024-08-02

PDF

Abstract: The construction of the PNT system is a crucial research topic in communication and navigation. Developing a comprehensive PNT system compatible with different types of PNT means and providing better flexibility and environmental adaptability has become an important topic that can be completed on time. The emergence and development of the 5G and BeiDou systems provide new ideas and guidance for the PNT system to be more comprehensive and flexible. Accordingly, this paper proposes an AOS-RAKF method based on the combined GNSS+5G data to realize high-precision localization estimation in urban complex environments. The algorithm mainly consists of two main modules. They are AOS-based 5G base station measurement data optimization and combined GNSS+5G positioning based on the AOS-RAKF algorithm. The AOS-based 5G base station measurement data optimization module achieves better observation data re-selection using adaptive optimal selection factors. The combined GNSS+5G positioning utilizes the optimized 5G data and GNSS to establish a coupled structural model to achieve high-accuracy localization of the mobile vehicle using the RAKF method. The results of semi-physical simulation tests show that the proposed AOS-RAKF method significantly improves the positioning accuracy in complex urban environments compared to GNSS, single 5G, and traditional combined GNSS+5G positioning using raw measurement data.

Key words: 5G positioning, GNSS, combined GNSS+5G positioning, adaptive optimal selection algorithm, disparity resistant adaptive Kalman filtering algorithm

CLC Number: