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�������պ����ѧѧ�� 2008, Vol. 34 Issue (05) :533-536    DOI:
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Method of any two-position alignment based on predictive filter for SINS
Gong Xiaolin, Fang Jiancheng*
School of Instrument Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

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ժҪ ��Խ������Ե���ϵͳ(SINS,Strapdown Inertial Navigation System)�ڴ�ʧ׼������µij�ʼ��׼����,�������ڼ�����Ԫ�����ģ�͵ķ������˲�����,�����һ�ֻ���ģ��Ԥ���˲�(MPF, Model Predictive Filter)����չ�������˲�(EKF, Extended Kalman Filter)���ϵĵ�������˫λ�ó�ʼ��׼����.�÷��������ֹ������������Ϊģ�����,����ʵʱ���Ʋ�����ϵͳģ��,�����״̬���Ƶľ���,���˷��˽�ģ��������Ϊ��˹�������ľ�����.���������������,�÷�����Ч�����SINS��̬���ǵĹ��ƾ���,����Ҳ������ϵͳ״̬������ά��,����˶�׼�����ʵʱ��.
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Abstract�� Aiming at the initial alignment of strapdown inertial navigation system(SINS) with a large azimuth misalignment angle, the nonlinear mathematics model based on additive quaternion error(AQE) equations was established. And any two-position alignment method based on model predictive filter(MPF) and extended Kalman filter(EKF) was proposed. In this method, parts of inertial element errors were regarded as the model error, and estimated as part of the solution. The model error was not limited to Gaussian noise characteristics, and the algorithm could be implemented on-line to both filter noisy measurements and estimate state trajectories. The results of tests show that this method has better precision and faster convergence of all misalignment angles especially the azimuth one than that of EKF. Furthermore, this method improves the alignment-s real time by reducing the number of states.
Keywords�� inertial navigation systems   alignment   prediction   nonlinear filtering     
Received 2007-05-11;
Fund:

����863����������Ŀ(2006AA12A108); ������Ȼ��ѧ����������Ŀ(60602047)

About author: ������(1980-),Ů,�½�������,��ʿ��,gongxiaolin@sina.com.
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������, ������.����Ԥ���˲��Ľ����ߵ�����˫λ�ö�׼����[J]  �������պ����ѧѧ��, 2008,V34(05): 533-536
Gong Xiaolin, Fang Jiancheng.Method of any two-position alignment based on predictive filter for SINS[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2008,V34(05): 533-536
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