Zeng, Q.H., Chen, W.N., Liu, J.Y. and Wang, H.Z. (2017) An Improved Multi-Sensor Fusion Navigation Algorithm Based on the Factor Graph. Sensors, 17, Article No. 641.
https://doi.org/10.3390/s17030641

has been cited by the following article:

• TITLE: Personnel Localization Method in Transformer Substation Based on Factor Graph

  AUTHORS: Haifei Yang, Yuntao Zhou, Huaijun Li, Baojun Wu, Fuchao Liu

  KEYWORDS: Personnel Positioning, Factor Graph, SINS/GNSS, Gauss-Newton Iteration, Information Fusion

  JOURNAL NAME: Journal of Computer and Communications, Vol.11 No.8, August 25, 2023

  ABSTRACT: A SINS/GNSS location method based on factor diagram is proposed to meet the requirement of accurate location of substation construction personnel. In this paper, the inertial autonomous positioning, carrier motion information acquisition and satellite positioning technologies are integrated. The factor graph method is adopted to abstract the measurement information received by inertial navigation and satellite into factor nodes, and the state information into variable nodes, so as to construct the SINS/GNSS construction personnel positioning fusion factor graph model. The Gauss-Newton iterative method is used to implement the recursive updating of variable nodes, and the optimal estimate of the location information of the construction personnel is calculated, which realized the high precision location of the construction personnel. The factor graph method is verified by pedestrian navigation data. The results show that the factor graph method can continuously and stably output high-precision positioning results, and realize non-equidistant fusion of SINS and GNSS. The positioning accuracy is better than Kalman filter algorithm, and the horizontal positioning accuracy is less than 1 m. Therefore, the factor graph method proposed can provide accurate location information for substation construction personnel.