Frequency-domain identification of continuous-time ARMA models from sampled data

This paper treats direct identification of continuous-time autoregressive moving average (CARMA) noise models. The approach has its point of origin in the frequency domain Whittle likelihood estimator. The discreteor continuoustime spectral densities are estimated from equidistant samples of the output. For low sampling rates the discrete-time spectral density is modeled directly by its continuous-time spectral density using the Poisson summation formula. In the case of rapid sampling the continuous-time spectral density is estimated directly by modifying its discrete-time counterpart.