A practical formulation is proposed for aircraft parameter estimation using the filter-error method, which is a maximum likelihood estimator for dynamic systems with both process noise and measurement noise. The novelty of the proposed formulation is that by accurately estimating the measurement noise covariance matrix using a time series analysis method, the remaining unknowns (which include the unknown parameters in the state-space matrices and the process noise covariance matrix) become decorrelated and can be estimated simultaneously in a straightforward manner. The approach is demonstrated using simulation data and flight test data from a subscale airplane. Results indicate that the proposed algorithm can produce accurate modeling results when both measurement noise and process noise are present in the data.


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    Title :

    Aircraft Parameter Estimation Considering Process and Measurement Noise


    Contributors:

    Published in:

    Journal of Aircraft ; 62 , 2 ; 288-299


    Publication date :

    2025-03-01




    Type of media :

    Conference paper , Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






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