Minimum entropy deconvolution of pulse-echo signals acquired from attenuative layered media

In this article deconvolution of ultrasonic pulse-echo data acquired from a ttenuative layered media is considered. The problem is divided in two subpr oblems: treating the sparse reflection sequence caused by the layered struc ture of the media and treating the frequency-dependent attenuation The firs t subproblem is solved by means of joint maximum a posteriori estimation of the assumed zero mean, white, nonstationary reflection sequence and its co rresponding sequence of unknown standard deviations. This approach leads to an algorithm that seeks minimum entropy solutions for the reflection seque nce and therefore the algorithm serves as a novel link between the classica l Wiener filter and methods for sparse or minimum entropy deconvolution. Th e second subproblem is solved by introducing a new signal processing-orient ed, linear discrete-time model for frequency-dependent attenuation in isotr opic and homogeneous media. The deconvolution algorithm is tested using sim ulated data and its performance for real normal incidence pulse-echo data f rom a composite material is also demonstrated. The results show that the al gorithm, in combination with the attenuation model, yields estimates that r eveal the internal structure of the composite and, thus, simplify the inter pretation of the ultrasonic data. (C) 2001 Acoustical Society of America.