GNSS Fault Tolerant Navigation Algorithm Based on Factor Graph Optimized Batch Covariance Estimation

AbstractIn the navigation and positioning process of global navigation satellite system (GNSS) in complex environment, due to occlusion, multipath effect and other faults, the navigation and positioning efficiency of GNSS will be reduced. Aiming at the problem that GNSS system is insensitive to fault tolerance and robust, a batch covariance estimation (BCE) navigation algorithm based on factor graph optimization is proposed. In this paper, firstly, by constructing the factor graph model of GNSS observation data, the graph optimization algorithm is applied to GNSS navigation to improve the navigation accuracy. Then, a BCE algorithm based on factor graph is proposed for GNSS fault, and the operation flow is designed to improve the navigation robustness. Finally, GNSS measurement data with different performance are used for simulation, and noise is added to the data to evaluate the method proposed in this paper. The results show that the BCE algorithm based on factor graph is better than the traditional methods in positioning accuracy and fault tolerance, especially in the case of low-performance measurement, which can significantly reduce the positioning error, and has the ability of fault tolerance when there are faults in the data.KeywordsGNSSBatch covariance estimationNavigation