Sensor selection from independence graphs using submodularity

In this paper we develop a framework to select a subset of sensors from a field in which the sensors have an ingrained independence structure. Given an arbitrary independence pattern, we construct a graph that denotes pairwise independence between sensors, which means those sensors can operate simultaneously. The set of all fully-connected subgraphs (cliques) of this independence graph can form a set of matroid constraints over which we maximize a submodular objective function. Since we choose the objective function to be submodular, the algorithm returns a near-optimal solution with approximation guarantees. We also argue that this framework generalizes to any network with a defined independence structure between sensors, and intuitively models problems where the goal is to gather information in a complex environment. We apply this framework to ping sequence optimization for active multistatic sonar arrays by maximizing sensor coverage and not only achieve significant performance gains compared to conventional round-robin sensor selection, but approach optimal performance as well.