Application of wavelet transforms to detection, estimation, modeling, and remote sensing in underwater acoustics

Abstract

It follows from fundamental acoustics that acoustic waves that have been reflected from boundaries or scatterers that are in relative motion in respect to the transmitter/receiver suffer propagation delays and time-scale dilations. Physical and kinematic parameters of distributed, moving scatterers can be estimated using continuous wavelet transforms. For this reason and for the reason that wavelet transform techniques lead to effective modeling of time and space varying media by wideband spreading and scattering functions, continuous wavelet transforms are natural tools for detection and estimation of wideband acoustic signals that have propagated through complex multipath propagation and scattering channels. Wideband spreading functions and scattering functions can be used in model-based environmentally adaptive signal processors. In remote sensing, wavelet transforms are effective for identification, parameter estimation, tracking, and systhesis of distributed acoustic scatterers. Other applications of continuous wavelet transforms include implementation of log-likelihood detectors of distributed scatterers by wideband acoustic signals and acoustic imaging of underwater objects. [This work was supported by The Office of Naval Research, sponsored by Dr. Kam W. Ng, Code ONR 333.]