Abstract

The SCAT (spectrogram correlation and transformation) model of biosonar in bats represents FM broadcasts and echoes as spectrographs with an integration time of 300–400 μs. The model then mimics signal processing by bats with two parallel computational paths: (1) determination of the delay of echo spectrograms using delay lines and coincidence detectors, and (2) deconvolution of the echo spectrum to determine delay separations smaller than the integration-time window [Saillant et al., J. Acoust. Soc. Am. (1993)] to produce high-resolution echo-delay images. The new, binaural version of the SCAT model receives broadcasts and echoes at two ‘‘ears’’ and uses binaural algorithms to produce range/azimuth sonar images. The model incorporates several stages of binaural interactions that facilitate different functions including determination of azimuth itself, enhancement of target detection, and separation of adaptive imaging from these other functions. The model produces images that locate the principal glints in complex targets from only a few sonar broadcasts without having to sample many different target aspect angles. [Work supported by ONR and NSF.]

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