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Novel algorithm for geomagnetic navigation
Abstract：To solve the highly nonlinear and non-Gaussian recursive state estimation problem in geomagnetic navigation, the unscented particle filter (UPF) was introduced to navigation system. The simulation indicates that geomagnetic navigation using UPF could complete the position estimation with large initial horizontal position errors. However, this navigation system could only provide the position information. To provide all the kinematics states estimation of aircraft, a novel autonomous navigation algorithm,named unscented particle and Kalman hybrid navigation algorithm (UPKHNA), was proposed for geomagnetic navigation. The UPKHNA used the output of UPF and barometric altimeter as position measurement, and employed the Kalman filter to estimate the kinematics states of aircraft. The simulation shows that geomagnetic navigation using UPKHNA could provide all the kinematics states estimation of aircraft continuously, and the horizontal positioning performance is better than that only using the UPF. 作者： Author： LI Ming-ming LU Hong-qian YIN Hang HUANG Xian-lin 作者單位： Center for Control Theory and Guidance Technology,Harbin Institute of Technology,Harbin 150001,China 期 刊： 中南大學(xué)學(xué)報(bào)（英文版） EISCI Journal： JOURNAL OF CENTRAL SOUTH UNIVERSITY OF TECHNOLOGY(ENGLISH EDITION) 年，卷(期)： 2011, 18(3) 分類號(hào)： V249.32 Keywords： autonomous navigation geomagnetic navigation unscented particle filter Kalman filter kinematics state estimation 機(jī)標(biāo)分類號(hào)： V44 P22 機(jī)標(biāo)關(guān)鍵詞： navigation system kinematics autonomous navigation the Kalman filter state estimation particle filter UPF performance initial However hybrid better novel 基金項(xiàng)目： The Fundamental Research Funds for the Central Universities of China【Novel algorithm for geomagnetic navi】相關(guān)文章：
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