In recent years,the Factor Graph Optimization(FGO)algorithm has gained a great attention in the feld of integrated navigation owing to its better positioning performance than the traditional flter-based approaches.How...In recent years,the Factor Graph Optimization(FGO)algorithm has gained a great attention in the feld of integrated navigation owing to its better positioning performance than the traditional flter-based approaches.However,the practical application of the FGO algorithm remains challenging due to its signifcant computational complexity and processing time consumption,especially for the case of limited storage and computation resources.In order to overcome the problem,we frst conduct a thorough analysis of the factor graph model for the Global Navigation Satellite System/Inertial Navigation System(GNSS/INS)integrated navigation.Then,based on the Incremental Smoothing and Mapping(iSAM),an Optimized iSAM(OiSAM)algorithm is proposed to efciently solve the optimization problem in FGO,with reducing computational load and required memory resources.For the re-linearization problem,we propose a novel Adaptive Joint Sliding Window Re-linearization(A-JSWR)algorithm combining periodic and on-demand re-linearization to further improve the efciency of OiSAM.Finally,the OiSAM-FGO method utilizing OiSAM and A-JSWR is presented for the GNSS/INS integrated navigation.The experiments on real-world datasets demonstrated that the OiSAM-FGO can reduce the time consumption of the optimization procedure by up to 52.24%,while achieving a performance equivalent to that of the State-of-the-Art(SOTA)FGO method and superior to the Extended Kalman Filter(EKF)method.展开更多
文摘In recent years,the Factor Graph Optimization(FGO)algorithm has gained a great attention in the feld of integrated navigation owing to its better positioning performance than the traditional flter-based approaches.However,the practical application of the FGO algorithm remains challenging due to its signifcant computational complexity and processing time consumption,especially for the case of limited storage and computation resources.In order to overcome the problem,we frst conduct a thorough analysis of the factor graph model for the Global Navigation Satellite System/Inertial Navigation System(GNSS/INS)integrated navigation.Then,based on the Incremental Smoothing and Mapping(iSAM),an Optimized iSAM(OiSAM)algorithm is proposed to efciently solve the optimization problem in FGO,with reducing computational load and required memory resources.For the re-linearization problem,we propose a novel Adaptive Joint Sliding Window Re-linearization(A-JSWR)algorithm combining periodic and on-demand re-linearization to further improve the efciency of OiSAM.Finally,the OiSAM-FGO method utilizing OiSAM and A-JSWR is presented for the GNSS/INS integrated navigation.The experiments on real-world datasets demonstrated that the OiSAM-FGO can reduce the time consumption of the optimization procedure by up to 52.24%,while achieving a performance equivalent to that of the State-of-the-Art(SOTA)FGO method and superior to the Extended Kalman Filter(EKF)method.
