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Experimental audible sonar to model echolocation by the blind

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Some blind humans echolocate by emitting palatal clicks and processing echoes, even when there is temporal emission/echo overlap (EEO). Our previous work indicates that high frequencies in the emission that travel directly to the ears are attenuated and, when high frequencies are heard, they come from target echoes. Binaural processing of these high frequency components in the EEO signals provide target range and bearing. Our experiments with 3D-printed parabolic pinnae and a speaker emitter indicate that while the high frequency components are important for object classification, the low frequencies in the emission provide more robust bearing localization because pinna diffraction effects are reduced. Classifying targets with EEO signals requires analysis in the power spectral domain because of the phase insensitivity of hearing. The power spectrum Fourier inverse estimates the autocorrelation function of the target reflector sequence. Robust autocorrelation estimates occur when the emission and echo contain comparable energies. Our experiments demonstrate that the echo energy varies with target type (e.g., planar or cylindrical) and the optimum range for classification depends on the target and itself forms a target classification feature.
Title: Experimental audible sonar to model echolocation by the blind
Description:
Some blind humans echolocate by emitting palatal clicks and processing echoes, even when there is temporal emission/echo overlap (EEO).
Our previous work indicates that high frequencies in the emission that travel directly to the ears are attenuated and, when high frequencies are heard, they come from target echoes.
Binaural processing of these high frequency components in the EEO signals provide target range and bearing.
Our experiments with 3D-printed parabolic pinnae and a speaker emitter indicate that while the high frequency components are important for object classification, the low frequencies in the emission provide more robust bearing localization because pinna diffraction effects are reduced.
Classifying targets with EEO signals requires analysis in the power spectral domain because of the phase insensitivity of hearing.
The power spectrum Fourier inverse estimates the autocorrelation function of the target reflector sequence.
Robust autocorrelation estimates occur when the emission and echo contain comparable energies.
Our experiments demonstrate that the echo energy varies with target type (e.
g.
, planar or cylindrical) and the optimum range for classification depends on the target and itself forms a target classification feature.

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