Wavelet multi-resolution analysis aided adaptive Kalman filter for SINS/GPS integrated navigation in guided munitions

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Abstract

SINS/GPS integrated navigation requires solving a set of nonlinear equations. In this case, the new method based on wavelet multi-resolution analysis (WMRA) aided adaptive Kalman filter (AKF) for SINS / GPS integration for aircraft navigation are proposed to perform better than the classical. The WMRA is used to compare the SINS and GPS position outputs at different resolution levels. These differences represent, in general, the SINS errors, which are used to correct for the SINS outputs during GPS outages. The proposed scheme combines the estimation capability of AKF and the learning capability of WMRA thus resulting in improved adaptive and estimation performance. The simulations show that good results in SINS/GPS positioning accuracy can be obtained by applying the new method based on WMRA and AKF. © 2011 Springer-Verlag.

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Cai, L., Kong, F., Chang, F., & Zhang, X. (2011). Wavelet multi-resolution analysis aided adaptive Kalman filter for SINS/GPS integrated navigation in guided munitions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7003 LNAI, pp. 455–462). https://doi.org/10.1007/978-3-642-23887-1_58

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