Model based time-frequency estimation of ultrasonic echoes for NDE applications

Modeling the ultrasonic signals in terms of the Gaussian echoes assures a solution for signal parameters and a technique for time-frequency representation. In this study, the parameter estimation is addressed using iterative Maximum A Posteriori (MAP) estimation algorithms. To reduce the computational complexity, we have developed a divide-and-conquer estimation procedure. Upon estimation, we have explored the merits of this model-based technique for time-frequency analysis of ultrasonic echoes. In particular, we are presenting ultrasonic experimental data where the microstructure scattering echoes dominate the flaw echoes (SNR is about 0 dB). This type of data is used to demonstrate the effectiveness of model based time-frequency representation over conventional techniques such as Wigner-Ville distribution and short-time Fourier transform