Design of sparse relative sensing networks

This paper considers the problem of designing sparse relative sensing networks (RSN) subject to a given ℌ_∞-performance constraint. The topology design considers homogeneous and heterogeneous agents over weighted graphs. We develop a computationally efficient formulation of the sparse topology design via a convex ℓ₁-relaxation. This makes the proposed algorithm attractive for practical applications. We also demonstrate how this relaxation can be used to embed additional performance criteria, such as maximization of the algebraic connectivity of the RSN.