Instantaneous frequency analysis of ultrasound Doppler signal using Bayesian probability.
Asif Mehmood, Paul M. Goggans, James M. Sabatier · The Journal of the Acoustical Society of America · 2009
In ultrasonic Doppler vibrometry systems, acoustic returned from a moving target is frequency modulated by the components of the target’s velocity in the direction of the system’s co-located ultrasonic transducers. Because of this, instantaneous frequency (IF) analysis of the receiver transducer output can be used to reveal the velocities of moving components. In this paper, an IF estimation algorithm using Bayesian probability theory is presented. The acoustic returns are represented by suitable localized models that are constructed on the basis of a number of moving components of the target. Then the posterior probabilities of these localized models are computed and compared to determine which model best describes the data under observation. Once the preferred model is chosen, then its parameters are estimated. Our IF estimation method performs parameter estimation and model selection simultaneously, and extends to instantaneous estimation of these nonstationary signals. The calculations are implemented using Markov chain Monte Carlo in conjunction with thermodynamic integration with simulated annealing to draw samples from the joint posterior probability for the model and the parameters. Monte Carlo integration is then used to approximate the marginal posterior probabilities for all the parameters. The performance of this method is demonstrated by simulated and experimental results.