Signal processing for target recognition in biosonar

The rotated wavelet transform permits recursive delay-and-stun beamforming with a sparsely sampled synthetic aperture constructed with a moving multibeam sonar system and is a generalization of wavelet and Radon transforms.

Abstract

Some properties of biological sonar systems are reviewed along with corresponding signal processing techniques. Relevant target representations appear to involve time-frequency or range-Doppler distributions and their projections as well as images derived from echoes observed at different positions. Target recognition can occur v via association of echo features derived from such representations, e.g. by using spatially registered feature maps. Informative features can be obtainedfrom sequential estimation of a vision-like acoustic image, i.e. a high-resolution representation of target reflectivity as a function of azimuth, elevation, and range. Such an image can be obtained with a rotated wavelet (line segment) transform, which is a generalization of wavelet and Radon transforms.The rotated wavelet transform permits recursive delay-and-stun beamforming with a sparsely sampled synthetic aperture constructed with a moving multibeam sonar system. The basis functions for the transform are rotated space-time transmission patterns similar to those used by echolocating dolphins.