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.
|Number of pages||4|
|Journal||Proceedings - IEEE International Symposium on Circuits and Systems|
|State||Published - 1995|
|Event||Proceedings of the 1995 IEEE International Symposium on Circuits and Systems-ISCAS 95. Part 3 (of 3) - Seattle, WA, USA|
Duration: 30 Apr 1995 → 3 May 1995