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Volume 45 Issue 11
Nov.  2023
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LIU Xiaohui, WANG Yichen, WEN Chao, LI Zongnan. Global Navigation Satellite System/Strapdown Inertial Navigation System Integrated Navigation Algorithm in Complex Urban Environment[J]. Journal of Electronics & Information Technology, 2023, 45(11): 4150-4160. doi: 10.11999/JEIT230834
Citation: LIU Xiaohui, WANG Yichen, WEN Chao, LI Zongnan. Global Navigation Satellite System/Strapdown Inertial Navigation System Integrated Navigation Algorithm in Complex Urban Environment[J]. Journal of Electronics & Information Technology, 2023, 45(11): 4150-4160. doi: 10.11999/JEIT230834

Global Navigation Satellite System/Strapdown Inertial Navigation System Integrated Navigation Algorithm in Complex Urban Environment

doi: 10.11999/JEIT230834
Funds:  The National Natural Science Foundation of China(U20A20193)
  • Received Date: 2023-08-02
  • Rev Recd Date: 2023-11-05
  • Available Online: 2023-11-14
  • Publish Date: 2023-11-28
  • In order to solve the problem that the Global Navigation Satellite System (GNSS) signal is frequently unlocked or rejected in complex urban environment, which has great influence on the navigation accuracy and robustness of GNSS/ Strapdown Inertial Navigation System (SINS) integrated navigation system, an improved factor graph filtering method is proposed in this paper. Firstly, GNSS receiver internal parameters are used to construct signal error identification function to estimate the performance of signal measurement at real time in the situation of multipath interference and occlusion. Simultaneously, zero-velocity update factor is constructed by the carrier motion constraint to update the system state under the condition of GNSS rejection. The experimental results show that compared with the classical factor graph method, the improved factor graph method can improve the positioning accuracy by 63.50% and the velocity measurement accuracy by 42.26% in complex environment with lower storage and computational complexity. The method is especially suitable for the scenarios with strong constraints on navigation accuracy, hardware resources and real-time performance in urban vehicle assisted driving navigation equipment.
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