Embedded Low Power Signal Processing for Passive Acoustic Monitoring

This project will attempt to explore the solution space around a number of key issues related to passive underwater acoustic monitoring. Namely the mitigation of acoustic flow noise in turbulent environments, digital compression techniques for underwater acoustic data and the implementation of real time signal processing algorithms related to the detection of marine mammals on ultra low power processors.

Faculty Supervisor:

Jean Francois Bousquet

Student:

Graham McIntyre

Partner:

Turbulent Research Inc.

Discipline:

Engineering - computer / electrical

Sector:

Environmental industry

University:

Dalhousie University

Program:

Accelerate

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