Q-Markov Cover identification with frequency partition for modal analysis of Hubble telescope flight data

In this paper, we present modal analysis results of Hubble space telescope flight data by a state space time-domain identification algorithm, called Q-Markov Cover (Q-Markov Covariance Equivalent Realization). The identification algorithm obtains a system state space model which matches the first Q Markov parameters and covariance parameters of the physical system generating the output data. The algorithm was applied to Hubble space telescope flight data to obtain a state space model for the telescope under an unknown disturbance in orbit. The flight data were partitioned into high and low frequency components for Q-Markov Cover modeling, to avoid some computational difficulties of the Q-Markov Cover algorithm. This identification revealed more than 20 modal resonances within the bandwidth of the attitude control system.

Q-Markov Cover identification with frequency partition for modal analysis of Hubble telescope flight data Conference Paper