Signal Processing and Control of a long-range Unmanned Surface Vehicle for Cetacean Detection in the Antarctic and Southern Sea

Abstract

A good proxy of overall marine ecosystem health is the abundance and state of marine mammal populations. These ecosystems can be impacted by various factors including but not limited to climate change and human activities. However, the effective monitoring and management of marine living resources - where these living organisms inhabit a vast, mainly inaccessible and hostile environment - requires innovation and the use of the best available technologies and methods [1]. Specifically, monitoring of cetacean populations in the Antarctic and Southern Ocean prove to be very difficult due to the sheer remoteness and harshness of the area.

Systems relying on acoustic signals have an effective reach which can exceed thousands of meters. Therefore, various studies have implemented passive acoustic monitoring (see for instance [2] and [3]) and found these techniques to be very effective, while not causing any significant environmental harm or damage when studying studying aquatic animals and their environment.

Another field of research is the research and development of unmanned surface vehicles. Unmanned surface vehicles have been developed for many diverse applications, ranging from military use, to environmental monitoring and sampling. A very inspiring case study is the recent circumnavigation of Antarctica, with a wind-powered unmanned surface vehicle, collecting data on wind, temperature, ocean currents, salinity, pH, chlorophyll, as well as atmospheric and dissolved gasses.

?The aim of this project is twofold. The first aim is to investigate, research and design control algorithms for a fixed sail unmanned surface vehicle, with the aim of long-range missions to the Southern Sea and Antarctica. The second aim is to investigate, research and design detection algorithms for Cetacean vocalisations, making use of passive acoustic monitoring as a dedicated sensor pack on the unmanned surface vehicle.