Balanced sensor management across multiple time instances via l-1/l-infinity norm minimization

In this paper, we propose a solution to the sensor management problem over multiple time instances that balances the accuracy of the sensor network estimation with its utilization. We show how this problem reduces to a binary optimization problem for which we give a convex relaxation based solution that involves the minimization of a regularized ℓ∞ reweighted ℓ1 norm. We show experimentally the behavior of the proposed algorithm and compare it with previous methods from the literature.