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Sensors 2018, 18(2), 659; https://doi.org/10.3390/s18020659

Application of Improved 5th-Cubature Kalman Filter in Initial Strapdown Inertial Navigation System Alignment for Large Misalignment Angles

Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
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Received: 22 December 2017 / Revised: 20 February 2018 / Accepted: 21 February 2018 / Published: 23 February 2018
(This article belongs to the Section Physical Sensors)
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Abstract

In view of the fact the accuracy of the third-degree Cubature Kalman Filter (CKF) used for initial alignment under large misalignment angle conditions is insufficient, an improved fifth-degree CKF algorithm is proposed in this paper. In order to make full use of the innovation on filtering, the innovation covariance matrix is calculated recursively by an innovative sequence with an exponent fading factor. Then a new adaptive error covariance matrix scaling algorithm is proposed. The Singular Value Decomposition (SVD) method is used for improving the numerical stability of the fifth-degree CKF in this paper. In order to avoid the overshoot caused by excessive scaling of error covariance matrix during the convergence stage, the scaling scheme is terminated when the gradient of azimuth reaches the maximum. The experimental results show that the improved algorithm has better alignment accuracy with large misalignment angles than the traditional algorithm. View Full-Text
Keywords: initial alignment; large misalignment angle; fifth-degree cubature Kalman filter; fading memory index weighting initial alignment; large misalignment angle; fifth-degree cubature Kalman filter; fading memory index weighting
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Wang, W.; Chen, X. Application of Improved 5th-Cubature Kalman Filter in Initial Strapdown Inertial Navigation System Alignment for Large Misalignment Angles. Sensors 2018, 18, 659.

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