A two-network deep learning system for active sonar, separating angle estimation from distance estimation, beats classical beamforming and spectrogram classifiers on simulated data.
The model was trained for 20 epochs with an initial learning rate of 1 × 10−4 using the Adam optimizer
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Angle-distance decomposition based on deep learning for active sonar detection
A two-network deep learning system for active sonar, separating angle estimation from distance estimation, beats classical beamforming and spectrogram classifiers on simulated data.