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Abstract

Apparatus for detecting sonar signals embedded in noise includes a neural network trained to detect signals in response to the slope of amplitude rank ordered noise corrected powers. A detector detects an analog waveform. Means samples and digitizes the analog waveform to obtain digital samples which in turn are passed through a cosine window. The digital samples are Fourier transformed into conjugate sets of complex numbers representing amplitude and phase. One conjugate set of the complex numbers are discarded, and the remaining complex numbers ranked according to frequency. The sum of the square of the real and imaginary component of each of the remaining complex numbers in a frequency band are provided to obtain a corresponding series of representing estimated power ranked by frequency over the band. The noise contained in subbands of the band is estimated. Each estimated power is then divided by the estimated noise of the subband containing the estimated power to obtain corresponding noise corrected powers, which are ranked ordered according to amplitude. The amplitude rank ordered noise powers are provided to corresponding inputs of the neural network.

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