Trellis-based deconvolution of ultrasonic echoes

A novel deconvolution algorithm is proposed for ultrasonic (us) echoes from layered materials. The basic idea is to model the reflectivity functions as well-defined sparse sequences and to perform a maximum-likelihood (ML) sequence estimation over the set of these sequences. A tree-based sequence estimation exhibits an exponentially growing complexity, but can in this case be converted into a trellis-based estimation with a linearly growing complexity. Deconvolution results of measured us-signals are given to confirm the theory. They demonstrate that the a priori knowledge introduced by the reduction of the solution space improves the deconvolution considerably.