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Extended Kalman filtering algorithm based on polynomial fitting
WU Hanzhou, SONG Weidong, XU Jingqing
Journal of Computer Applications    2016, 36 (5): 1455-1457.   DOI: 10.11772/j.issn.1001-9081.2016.05.1455
Abstract477)      PDF (567KB)(379)       Save
The data acquired by the satellite positioning receiver in the trajectory correction projectile must be filtered in real-time to predict the point. The calculation of traditional filtering method is time-consuming, and is difficult to meet the requirements of real-time filtering. A kind of extended Kalman filtering algorithm based on polynomial fitting was proposed. The data of projectile flight in the time interval was replaced by the fitting interpolation data. In this way the filter frequency could be reduced. Simulation results show that the computation time of the proposed method can be reduced by 7/8 compared to traditional extended Kalman filtering without reducing the filtering precision, and the real-time performance is improved. This method can provide important reference for the research of key technology of trajectory correction projectile. At the same time, the method can be applied to other filtering algorithms, and has a strong portability.
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