POLY-REFERENCE MODAL PARAMETERS IDENTIFICATION BASED ON MAXIMUM LIKELIHOOD ESTIMATOR

A frequency-domain modal parameters identification method based on maximum likelihood estimation is investigated considering stochastic noise. This method uses right matrix fraction description model of frequency response function. The noise covariance matrix is adopted as weighting function. The basis function in discrete time domain is utilized for improving numerical condition. First, the least square estimation is implemented to get the initial value of modal parameters. Then, the iterative optimization of Gauss-Newton method is carried out to get more precise identification result. A simulation case of GARTEUR model is employed to validate the method. Results show that the accuracy of modal parameters is improved obviously from maximum likelihood estimation method under high noise, especially for the damping ratio accuracy.