• Electronics Optics & Control
  • Vol. 28, Issue 2, 12 (2021)
WANG Ran and GAO Zhenxing
Author Affiliations
  • [in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2021.02.003 Cite this Article
    WANG Ran, GAO Zhenxing. Adaptive Kalman Filter Based Estimation of Aircraft Airflow Angles[J]. Electronics Optics & Control, 2021, 28(2): 12 Copy Citation Text show less

    Abstract

    Both attack angle and sideslip angle are important flight state parameters of aircraft.However,it is difficult for the atmospheric data system to accurately measure the airflow angles under the conditions of adverse weather,high attack angle or maneuvering flight.A method for estimation of aircraft airflow angle is studied based on flight data.Taking the external disturbances,the different data sampling frequencies,and the unknown statistical characteristics of flight data into account,the aircraft system state equation and measurement equation are established.The adaptive Kalman filtering algorithm based on the maximum likelihood criterion is integrated with the non-equal interval theory.Taking the turning and climbing flight of aircraft as an example,external disturbance is applied to estimate the attack angle and sideslip angle.Experimental results show that the algorithm has better estimation precision and higher robustness against external disturbance than the extended Kalman filtering algorithm and the unscented Kalman filtering algorithm.
    WANG Ran, GAO Zhenxing. Adaptive Kalman Filter Based Estimation of Aircraft Airflow Angles[J]. Electronics Optics & Control, 2021, 28(2): 12
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