To solve the problem of poor positioning accuracy of traditional vehicle navigation system caused by external interference or sensor failure in complex urban environments,an adaptive integrated navigation algorithm based on interactive multiple model factor graph optimization is proposed.The IMU/GNSS/LIDAR integrated navigation system model is constructed based on the factor graph optimization algorithm.The interactive multiple model is applied in the modeling process of sensor measurements and constructing variable nodes.The model update probability is used to optimize the sensor weights and the solution and update of the vehicle navigation system is realized based on the nonlinear optimization and incremental smoothing theory of factor graph algorithm.The experimental results show that compared with the adaptive factor graph optimization algorithm,the proposed algorithm can improve the positioning accuracy of vehicle navigation system in complex urban environments by 26.2%.
NETL
NSTL
万方数据
维普
