Pattern recognition application to underwater acoustics is a relatively less explored area, even though much study has been made of sonar signal detection. Recently, significant effort has been made of submarine transient signal analysis and classification. Various spectral and time domain features are considered for detection and event classification. Effective recognition requires signal segmentation. The use of entropy distance measure for waveform segmentation is then examined. The next pattern recognition application is the target motion analysis by using pattern matching idea in the estimation of target range, velocity, and bearing. Another application is in multipath ranging. An image processing technique is used to extract the significant tracks from the correlograms to provide a continuous estimate of time delay or range under a multipath environment. Major computer results reported earlier [C. H. Chen, Pattern Recog. J.16(6) (1983)] along with further results on transient signal analysis are presented. Other applications such as sonar recognition in fisheries are also examined. While the trend continues to be digital processing and system integration, the basic recognition issue remains to be the extraction of effective features from the preprocessed underwater acoustical data. [Work partially supported by NUSC at Newport, RI.]