Active identification of stochastic dynamic systems
Amirza Abdenov · 1998
It is necessary to know the covariance matrices of measurement noise and dynamic system noise, state and control matrices in order to estimate the optimal state vector. In this paper, algorithmic aspects of linear dynamic system active identification for optimal solution of the Kalman filter problem are considered. It is proposed to solve the input design task by using an input signal autocorrelation function in the time domain and an input signal spectral density in the frequency domain.