Identification of AR systems at a very low SNR using damped cosine model of autocorrelation function

This paper presents a new method for autoregressive (AR) system identification at a very low signal to noise ratio (SNR) using damped cosine model for the autocorrelation function of the noise-free, AR signal. The AR parameters are obtained directly from the estimated damped cosine model parameters. The simulation results show that the method can estimate the system parameters with high accuracy even at an SNR as low as −5 dB.