Feedforward neural network system for the detection and characterization of sonar signals with characteristic spectrogram textures
AssigneeAT&T Corp.
InventorsMichael C. Recchione, Anthony P. Russo
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Abstract
The present invention provides a method and system for characterizing the sounds of ocean captured by passive sonar listening devices. The present invention accomplishes this by first generating a spectrogram from the received sonar signal. The spectrogram is characterized in terms of textural features and signal processing parameters. The textural features and signal processing parameters are fed into a neural network ensemble that has been trained to favor specific features and/or parameters. The trained neural network ensemble classifies the signal as either Type-I or clutter.
Claims11
A method for characterizing a sonar signal captured by sonar listening devices, the method comprising the steps of:
- (1) characterizing a spectrogram generated from a sonar signal in terms of textural features and signal processing parameters;
- (2) inputting to a plurality of trained neural networks said textural features and said signal processing parameters of said spectrogram, wherein each of said plurality of trained neural networks is trained to favor a different subset of said textural features and said signal processing parameters;
- and
- (3) classifying components of said sonar signal as characteristic texture or clutter using said trained neural network.
An apparatus for characterizing the sounds of ocean captured by sonar listening devices, comprising:
- means for generating a spectrogram from a sonar signal;
- means for characterizing said spectrogram in terms of textural features and said signal processing parameters;
- and
- a plurality of neural networks trained to classify components of said sonar signal as characteristic texture or clutter based on said textural features and said signal processing parameters, wherein each of said plurality of neural networks has been trained to favor a subset of said textural features and said signal processing parameters.
Dependencies are inferred from the claim text.