Prediction of Bird Flapping Frequency Based on Least Squares Polynomial Fitting

Identifying the movement state of flying birds by scattered echoes is a hot topic in radar bird detection. At present, the quantitative relationship between flapping frequency and its dynamic electromagnetic scattering characteristics is not clear, which brings challenges to flying bird detection. In view of this, this paper proposes a correlation modeling method based on least squares polynomials for bird flapping frequency prediction. This method uses least squares polynomials to fit the scattering characteristic data and flapping frequency, and uses MAE, MRE and RMSE to verify the fitting accuracy and explore the optimal order that minimizes the error between the fitted curves and the data points. Numerical experimental results show that the correlation model constructed by this method can effectively predict flapping frequency. Further experiments show that the prediction results using third-order polynomials have the minimum error and maximum fitting accuracy and are the optimal order.