Journal of Geodesy and Geoinformation Science ›› 2021, Vol. 4 ›› Issue (2): 1-13.doi: 10.11947/j.JGGS.2021.0201

• Special Issue •     Next Articles

Performance Analysis of GNSS/MIMU Tight Fusion Positioning Model with Complex Scene Feature Constraints

Jian WANG1,2(),Houzeng HAN1(),Fei LIU1,2,Xin CHENG1   

  1. 1. School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 102616, China
    2. Research and Development Institute, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
  • Received:2020-09-15 Accepted:2021-01-15 Online:2021-06-20 Published:2021-07-02
  • Contact: Houzeng HAN;
  • About author:Jian WANG (1980—), male, PhD, professor, majors in geodesy and survey engineering, and the current research interests focus on GNSS positioning, integrated navigation and Indoor localization. E-mail:
  • Supported by:
    Youth Program of National Natural Science Foundation of China(41904029);Scientific Research Project of Beijing Educational Committee(KM202010016009)


In order to meet the requirements of high-precision vehicle positioning in complex scenes, an observation noise adaptive robust GNSS/MIMU tight fusion model based on the gain matrix is proposed considering static zero speed, non-integrity, attitude, and odometer constraint models. In this model, the robust equivalent gain matrix is constructed by the IGG-Ⅲ method to weaken the influence of gross error, and the on-line adaptive update of observation noise matrix is carried out according to the change of actual observation environment, so as to improve the solution performance of filtering system and realize high-precision position, attitude and velocity measurement when GNSS signal is unlocked. A real test on a road over 600km demonstrates that, in about 100km shaded environment, the fixed rate of GNSS ambiguity resolution in the shaded road is 10% higher than that of GNSS only ambiguity resolution. For all the test, the positioning accuracy can reach the centimeter level in an open environment, better than 0.6m in the tree shaded environment, better than 1.5m in the three-dimensional traffic environment, and can still maintain a positioning accuracy of 0.1m within 10s when the satellite is unlocked in the tunnel scene. The proposal and verification of the algorithm model show that low-cost MIMU equipment can still achieve high-precision positioning when there are scene feature constraints, which can meet the problem of high-precision vehicle navigation and location in the urban complex environment.

Key words: GNSS/MIMU; robust Kalman filter; constrained model; ambiguity resolution; navigation and positioning