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Underwater acoustic technologies are a key component for exploring thebehavior of marine megafauna such as sea turtles, sharks, and seals. Theanimals are marked with acoustic devices (tags) that periodically emit signalsencoding the device's ID along with sensor data such as depth, temperature, orthe dominant acceleration axis - data that is collected by a network ofdeployed receivers. In this work, we aim to optimize the locations of receiversfor best tracking of acoustically tagged marine megafauna. The outcomes of suchtracking allows the evaluation of the animals' motion patterns, their hours ofactivity, and their social interactions. In particular, we focus on how todetermine the receivers' deployment positions to maximize the coverage area inwhich the tagged animals can be tracked. For example, an overly-condenseddeployment may not allow accurate tracking, whereas a sparse one, may lead to asmall coverage area due to too few detections. We formalize the question ofwhere to best deploy the receivers as a non-convex constraint optimizationproblem that takes into account the local environment and the specifications ofthe tags, and offer a sub-optimal, low-complexity solution that can be appliedto large testbeds. Numerical investigation for three stimulated seaenvironments shows that our proposed method is able to increase thelocalization coverage area by 30%, and results from a test case experimentdemonstrate similar performance in a real sea environment. We share theimplementation of our work to help researchers set up their own acousticobservatory.

Design of an Optimal Testbed for Tracking of Tagged Marine Megafauna