Method for estimating parameters of multi-mode signals measured at SECIRA radars

The paper presents the algorithm for evaluating parameters of coherent scattering signals, which is based on the assessment of their parametric spectra by the well-known autoregression ARMA(10,10) model. The assessment consists of autoregression over 10 sequence members, moving average over residuals for 10 sequence members, and subsequent fitting of the resulting spectra with the sum of gaussian functions. The algorithm is a development of Burg’s method, previously proposed for the analysis of SuperDARN data. It differs from the method in the use of a more complex regression model, consideration of characteristics of the correlation function, and determination of three parameters for each peak (mode) — amplitude, Doppler velocity, and spectral width. Comparison shows that the best continuity between the parameters of multi-mode signals, obtained by new and standard signal processing methods, is provided by analysis of the mode with maximum integral power. The analysis has revealed that new and standard methods in the case of single-mode signals give close Doppler velocities. The multi-mode analysis presented in the paper increases the number of detected signals of various types, and can be employed to expand the diagnostic capabilities of SECIRA/SuperDARN radars, including automatic classification of each mode.