Title :
An integrated sensory-intelligent system for underwater acoustic signal-processing applications
Author :
Zaknich, Anthony
Author_Institution :
Univ. of Western Australia, Crawley, WA, Australia
Abstract :
A generic integrated sensory-intelligent system (ISIS) is developed for underwater acoustic signal-processing applications. ISIS constantly monitors the current acoustic channel conditions and smoothly integrates the outputs of the most appropriate signal-processing procedures or algorithms available to it for those conditions. The system is based on a generalization of a tuneable approximate piecewise linear (TAPL) model derived from the modified probabilistic neural network (MPNN). This model was designed to seamlessly integrate a set of local linear signal-processing algorithms within a given multidimensional data space. Depending on the input signal distortions, which are determined by environmental effects, ISIS automatically weighs and adds the outputs from a set of processing algorithms working in parallel. The weighting is related to the "closeness" of each algorithm to the sensed input signal characteristics or some other measured environmental state. A single tuning parameter is used to smoothly and seamlessly select appropriately among the parallel processing algorithm outputs. A very small tuning-parameter value selects the closest most appropriate algorithm output. At the other extreme, a fixed weighted average of all the algorithm outputs is produced with a very large value. Otherwise, a dynamic weighed average of all algorithm outputs is achieved with values in between. Some features and benefits of ISIS are demonstrated with an illustrative linear sweep chirp signal-detector estimation problem characterized by extremely variable Doppler conditions.
Keywords :
acoustic signal processing; correlators; intelligent sensors; neural nets; piecewise linear techniques; radial basis function networks; underwater sound; ISIS; MPNN; TAPL; correlator; dynamic weighed average; environmental input signal distortions; integrated sensory-intelligent system; linear sweep chirp signal-detector estimation; modified probabilistic neural network; multidimensional data space; radial basis function; signal estimation; tuneable approximate piecewise linear model; tuning parameter; underwater acoustic signal processing; variable Doppler conditions; Acoustic distortion; Algorithm design and analysis; Intersymbol interference; Multidimensional systems; Neural networks; Piecewise linear approximation; Piecewise linear techniques; Signal design; Signal processing; Underwater acoustics;
Journal_Title :
Oceanic Engineering, IEEE Journal of
DOI :
10.1109/JOE.2003.819796