It is well known that the characteristics of a sonar backscatter image depend on the bottom type.

Even to a novice user, the texture differences between images of rocks, sand, and mud are readily apparent.

Differences between silt and clay are less obvious.

Statistical processing can capture many of the pertinent details of the interaction between the sound and the bottom and of its vertical relief.

Multivariate statistics can then isolate those details that are rich in information about the bottom, producing feature vectors that contain the information necessary for accurate and reliable bottom classifications.

A new approach was developed that extracts information, not from the details of the vertical echo over time but, from the amplitudes and variability of backscatter and statistical characteristics at angles away from the vertical.