Abstract
A new non model-related algorithm that can perform the auto-piloting of the aircraft under all conditions is presented. For improving the precision of the loosely coupled GPS/SINS integrated navigation system, fusing data from a SINS and GPS hardware utilizes wavelet multi-resolution analysis (WMRA) and Radial Basis Function Neural Networks (RBFNN). 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 RBFNN model is then trained to predict the SINS position errors in real time and provide accurate positioning of the moving aircraft. The simulations show that good results in SINS/GPS positioning accuracy can be obtained by applying the new method based on WMRA and RBFNN.
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Chen, X., Zhu, X., Li, Z. (2007). Application for GPS/SINS Loosely-Coupled Integrated System by a New Method Based on WMRA and RBFNN. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2007. Lecture Notes in Computer Science, vol 4681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74171-8_39
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DOI: https://doi.org/10.1007/978-3-540-74171-8_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74170-1
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