Signal processing trade-offs for the representation and quality assessment of acoustic color signatures

Abstract

Acoustic color is a representation of an object, typically 2-D, which is constructed to show the evolution of the spectral response over the aspect of the object. The two natural axes for this representation are frequency and the aspect to the object. It is intuitive to assume finer resolution in both dimensions would lead to more information extractable for improved quality. However, with conventional linear track data collection methods, there is an inherent trade-off between signal processing decisions and the amount of information that can be utilized without loss of quality. In this work, this trade-off is investigated for an object with a simple geometry, and various quality metrics are discussed. For objects with spectral response that changes slowly over aspect, quality can be improved with methods such as synthetic aperture sonar processing. However, the effect of these processing decisions can depend on the type of object being represented. Other representation approaches as extensions of acoustic color will also be explored, such as time-evolving acoustic color that shows how the spectral response changes within a ping cycle.