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Proceedings Paper

Application of an improved adaptive Kalman filter to transfer alignment of airborne missile INS
Author(s): Chun-ming Xie; Yan Zhao; Ji-nan Wang
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Paper Abstract

Transfer alignment is an initialization of the missile INS prior to launch using data provided by master INS or GPS/INS system in aircraft. Generally, Kalman filter is applied to estimate misalignment attitude. Unfortunately, the Kalman filter provides optimal estimates only if the system model is accurate and filter noise is white and accurately obtained. Considering the complicated vibrated air environment, these demands can not be satisfied all the time. Therefore, after establishing a 12-state velocity matching transfer alignment model, an improved adaptive method is derived on the basis of the study on traditional adaptive Kalman filter such as Sage-Husa and intense adaptive filter. The improved adaptive filter is aimed at modifying the model and noise matrix with the process of filtering according to the practical measurement data. Numerical simulations show that with this improved adaptive filter under a "s" turn maneuver, transfer alignment Kalman filter keeps good working condition under large range of P, Q and R, and reaches good performance on estimating precise and convergent speed.

Paper Details

Date Published: 13 October 2008
PDF: 6 pages
Proc. SPIE 7129, Seventh International Symposium on Instrumentation and Control Technology: Optoelectronic Technology and Instruments, Control Theory and Automation, and Space Exploration, 71292F (13 October 2008); doi: 10.1117/12.807472
Show Author Affiliations
Chun-ming Xie, Beijing Univ. of Aeronautics and Astronautics (China)
Guilin Airforces Academy (China)
Yan Zhao, Beijing Univ. of Aeronautics and Astronautics (China)
Ji-nan Wang, Beijing Univ. of Aeronautics and Astronautics (China)
China Airborne Missile Academy (China)


Published in SPIE Proceedings Vol. 7129:
Seventh International Symposium on Instrumentation and Control Technology: Optoelectronic Technology and Instruments, Control Theory and Automation, and Space Exploration

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