INS/5G integrated navigation method based on improved EMD-CIIT denoising algorithm
This paper focuses on the inertial navigation system(INS)/5G integrated navigation system.Firstly,an improved thresholding algorithm called clear iterative empirical mode decomposition interval-thresholding(EMD-CIIT)is proposed to effectively enhance the signal-to-noise ratio(SNR)of inertial sensors and thereby improve the positioning accuracy of the integrated navigation system,which addresses the issue of low SNR in low-cost inertial sensors that impacts the accuracy of integrated navigation systems.Additionally,to address the issues of co-frequency interference,clock bias,and clock drift in 5G opportunity signals that cause abnormal pseudo-range values,a tightly-integrated navigation algorithm based on adaptive Kalman filtering is proposed.The proposed algorithm utilizes a 5G pseudo-range confidence scheme based on Mahalanobis distance to adjust the observation covariance matrix in real time,which mitigates the impact of abnormal pseudo-range values on positioning accuracy and further enhances the reliability of positioning.Finally,the effectiveness and superiority of the proposed solution tests are validated through numerical simulation tests and experimental methods.
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