Abstract
Acoustic color is a representation of the spectral response over aspect, typically in 2-D. The two natural axes for this representation are frequency and the aspect to the object. It is intuitive to assume finer resolution in the two 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, how the information distribution is affected with choices of representation domain will be presented. The quality metrics including resolution, signal-to-noise-ratio, and other metrics will be discussed in the context of various signal processing choices and parameters. 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.
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