Dr. Paul C. Hines was born and raised in Glace Bay, Cape Breton. From 1977-1981 he attended Dalhousie University, Halifax, Nova Scotia, graduating with a B.Sc. (Hon) in Engineering-Physics.
He joined the Defence Research Establishment Atlantic (now Defence R&D Canada - Atlantic), Dartmouth, Canada where he researched towed array self-noise. From 1985-1988, he attended the University of Bath, UK where he received his PhD in Physics. His research on acoustic scattering from ocean boundaries earned him the Chesterman Medal from the University for "Outstanding Research in Physics". Upon returning to DRDC Atlantic in 1989, he joined the Acoustic Countermeasures group to work on acoustic scattering and time spreading. From 1996 until 2003 he led several research groups that focused on experimentation and modeling to support sonar research. Since 2003 he has managed projects in Rapid Environmental Acoustics and Aural Classification for underwater acoustics and is currently Principal Scientist in the Underwater Sensing section at DRDC.
Dr. Hines is a Fellow of the Acoustical Society of America, a member of IEEE, and an Adjunct Professor at Dalhousie University's Dept. of Graduate Studies. He is a seasoned experimentalist and has been chief scientist for several collaborative international research trials. His present research interests include acoustic scattering, sound speed dispersion in the seabed, vector sensor processing, and the application of aural perception in humans, to target classification in sonar.
1. The application of aural perception in humans to active and passive sonar classification.
Humans have a remarkable ability to aurally classify transient acoustic signals - from a dog's bark to the slamming of a car door. Sonar experts have always relied to some extent on this ability to aurally classify sounds to assist in identification - this includes active sonars, in which an acoustic wave is transmitted and one listens to the received echo from a target, such as a submarine, and passive sonars in which one simply listens for signals of interest, such as a marine mammal call. This begs the questions, "How do humans discriminate between these sounds and can we develop a computer algorithm to do it?" In this presentation, we examine those questions, and present some rather pleasing results from an automatic aural classifier that was applied to active sonar target classification and to passive classification of marine mammal vocalizations.
2. Vector sensors: Over 40 and Still Hot (a Hot Topics lecture given at the 151st Meeting of the Acoustical Society of America)
Acoustic vector sensors and gradient arrays have been in use in underwater acoustics for more than 4 decades so one may wonder why they might be considered a "Hot Topic". The reason lies in the recent resurgence in their use. This in turn, is due primarily to major advances in engineering and signal processing that have been applied to these devices. Historically, theoretical gains have been difficult to achieve with these sensors due to their susceptibility to uncorrelated noise. That is to say, the very process of making a localized measurement of the vector acoustic field lowers the signal-to-noise ratio, relative to a simple pressure measurement. However, with today's advances in design, manufacturing, and digital signal processing, high-quality performance can be achieved in a very small package size. Moreover, the current interest in these devices isn't limited to underwater acoustic applications; rather it extends across a number of technical areas within the acoustics community. This presentation will begin with a gentle introduction to the theoretical foundation and history of these devices. Then some current applications in both underwater and airborne acoustics will be highlighted.