Optimum Signal Processing and Medium Characterization in the Time-Frequency and Wavelet Transform Domains

In underwater acoustic detection of nonstationary signals and characterization of the scattering it is advantageous to implement signal processors in time-frequency or timetimescale (wavelet transform) domains. By using reproducing kernel Hilbert space theory, this paper unifies optimum signal processing and medium characterization. Using wavelet transforms, the widely-used narrowband scattering function theory is extended to model wideband, nonstationary stochastic scattering and propagation channels. Solution of the inverse problem exploits recent developments of the group transform theory.

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