Determining the patterns of fish migration is critical to scientific studies both for the ecology of any given environment but also in forming sustainable fisheries. Knowledge of an ecosystem’s ecology is required in order to make changes to the environment, for the development of renewable energy structures for example. With new developments in unmanned vehicles and marine autonomy, solutions that give more fine scale and accurate data, over longer missions, are being developed. This paper describes the novel design of a low-cost autonomous surface vehicle for tracking the fine-scale movements of fish. This includes a sensor network capable of tracking fish using an autonomous system that navigates, processes sensor data and logs information. The sensors involve a network of acoustic hydrophones, using an acoustic tag that is surgically inserted into the fish. The vehicle’s autonomy is developed using both the Robotics Operating System (ROS) and the Mission Oriented Operating Suite (MOOS-IvP) in order to create a heterogeneous multi-platform system. Field trials using an array of hydrophones were used to show real-time processing of acoustic transducers for fish localisation. Simulations of the localisation display how this data is used to track and follow. Less intensive localisation methods are used for following in real-time, while more computationally expensive algorithms are applied post-mission for finer-scale localisation. We provide insight into the problems and solutions for developing a tracking system of this type, and discuss possible future emerging technologies related to autonomous marine missions.