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.
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This work was supported by China Natural Science Foundation Committee (60775023, 60975025), Natural Science Foundation Committee of Shandong Province of China (Z2005G03), and SRF for ROCS, SEM.
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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: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7003. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23887-1_58
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DOI: https://doi.org/10.1007/978-3-642-23887-1_58
Publisher Name: Springer, Berlin, Heidelberg
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