Non-myopic sensor scheduling for a distributed sensor network

When tracking a target in a sensor network with constrained resources, significant reductions in sensor communications and usage cost can be realized by using non-myopic sensor scheduling. The use of integer non-linear programming is beneficial for obtaining myopic sensor schedules. In this paper, we extend its benefits to a non-myopic sensor scheduling scenario consisting of a distributed network of bearing sensors. We formulate this problem, which we call the Leader Node Scheduling problem, as an integer non-linear programming problem with the objective of minimizing the total sensor usage and communications cost over a planning horizon subject to tracking error constraints per time step.