An algorithm of intelligent ship INS/GPS integrated navigation based on factor graph
For intelligent ships that depend solely on information obtained from a single perception sensor,it is difficult to meet the navigation demand for high precision and high reliability.For the problem,a data fusion method based on factor graph optimization is proposed,and the method combines data from inertial navigation system(INS)and global positioning system(GPS).The mechanical arrangement of INS is carried out according to the measurement model of the inertial measurement unit(IMU).Using pre-integration principle,the pre-integration factor nodes are constructed.The drift errors of gyroscopes and accelerometers are used to construct the drift factor nodes to correct the pre-integration results.An INS/GPS factor graph integrated navigation model is constructed by inserting GPS factors,and some navigation state variable nodes affected by new measurement factors are identified and updated.The optimal state estimation value is obtained by methods such as nonlinear optimization,and the multi-source perception information fusion is realized.The simulation results verify the effectiveness of the method.Compared with the common Kalman filter,the proposed method has better convergence performance when GPS signal fails.
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