Volume 107, Issue 5, May 2000
Index of content:
- ACOUSTIC SIGNAL PROCESSING 
Inverse problem solution techniques as applied to indirect in situ estimation of fish target strength107(2000); http://dx.doi.org/10.1121/1.428643View Description Hide Description
In situ indirect methods of fish target strength (TS) estimation are analyzed in terms of the inverse techniques recently applied to the problem in question. The solution of this problem requires finding the unknown probability density function (pdf) of fish target strength from acoustic echoes, which can be estimated by solving the integral equation, relating pdf’s of echo variable, target strength, and beam pattern of the echosounder transducer. In the first part of the paper the review of existing indirect in situ TS-estimation methods is presented. The second part introduces the novel TS-estimation methods, viz.: Expectation, Maximization, and Smoothing (EMS), Windowed Singular Value Decomposition (WSVD), Regularization and Wavelet Decomposition, which are compared using simulations as well as actual data from acoustic surveys. The survey data, acquired by the dual-beam digital echosounder, were thoroughly analyzed by numerical algorithms and the target strength and acoustical backscattering length pdf’s estimates were calculated from fish echoes received in the narrow beam channel of the echosounder. Simultaneously, the estimates obtained directly from the dual-beam system were used as a reference for comparison of the estimates calculated by the newly introduced inverse techniques. The TS estimates analyzed in the paper are superior to those obtained from deconvolution or other conventional techniques, as the newly introduced methods partly avoid the problem of ill-conditioned equations and matrix inversion.
107(2000); http://dx.doi.org/10.1121/1.428644View Description Hide Description
Coherent multi-frequency matched-field processing is investigated using a matched-phase coherent matched-field processor. Its main difference from previous coherent processors is that the relative phases of the Fourier components contained within the recorded signal are not assumed to be known a priori. Rather they are considered free parameters that can be determined using a global functional minimization algorithm. Additionally, this processor uses only the cross-frequency terms, making it less susceptible to the detrimental effects of ambient noise; in one example, this processor shows a five decibel improvement over a similar coherent processor. Along with its increased sensitivity with respect to the broadcast source levels, this coherent processor exhibits superior range resolution as compared with multi-frequency incoherent processors, due to the cross-frequency interference of the vertical eigenmodes. Within this work we explore the efficacy of the algorithms used to determine the relative phases along with the performance of the matched-phase coherent processor itself, performed within the context of data collected during an event from the SWellEx-96 experiment. Performance comparisons between this processor, an incoherent processor, and another coherent processor are demonstrated using this data set.
107(2000); http://dx.doi.org/10.1121/1.428645View Description Hide Description
Higher order statistical blind deconvolution methods are implemented for use in removing multipath distortion from passively received underwater acoustic transient signals. Using single channel data and simulations, it is demonstrated that a fourth order method based on cumulant maximization can work well if the associated multipath Green’s function is sufficiently “sparse.” The iterative method is parameterized by filter length, and while there is a range of values at which the best solutions are obtained with conventional convergence criteria, useful solutions exist across a much broader range of filter lengths if the iterations are not always allowed to proceed to convergence. The fourth order objective functional is generalized to arbitrary order, and the method is shown to also produce good results for the third order objective functional.