Optimal discovery of ambient acoustic noise field

We describe a problem in which a multi-agent acoustic sensing swarm seeks to characterize the ambient acoustic noise field as an input for selecting subsequent sensing locations. We develop a method for solving this problem by applying the Pontryagin Maximum Principle to determine an optimal control law and demonstrate this application on a single agent system. An algorithm is developed for solving the resulting mixed boundary value differential equations in real time by an eigenvalue decomposition method. This technique is demonstrated on a representative ambient acoustic noise field via simulation.

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