Integrated Navigation Algorithm Based on Interactive Multi-Model Square-Root Cubature Kalman Filter
To address the issue of reduced filtering accuracy in integrated navigation systems caused by variable noise interference,an algorithm based on interactive multi-model(IMM)and square-root cubature Kalman filter(SCKF)is proposed.The IMM-SCKF filtering algorithm employs multiple model sets and adjusts the probability of the sub-model while fusing the output,allowing it to simulate the actual noise covariance to a certain degree.Simu-lation and road test results show that the root mean square(RMS)error of the IMM-SCKF algorithm is superior to that of the traditional single-model CKF algorithm,effectively enhancing the reliability of the integrated navigation system.Compared to the traditional CKF algorithm,the IMM-SCKF algorithm reduced the RMS error in eastward,northward,and up speed errors by 52%,55%,and 30%,respectively,and the RMS error in position by 47%,60%,and 32%,respectively.The IMM-SCKF algorithm significantly improves the positioning accuracy and anti-interference ability of the system.
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