Structural cost-optimal design of sensor networks for distributed estimation
It offers a scalable approach to sensor network design for control engineers dealing with large-scale monitoring systems.
This work addresses cost optimization of sensor networks for distributed estimation under observability constraints, providing a polynomial solution for sensing cost and a 2-approximation for networking cost, applicable to large-scale systems.
In this letter we discuss cost optimization of sensor networks monitoring structurally full-rank systems under distributed observability constraint. Using structured systems theory, the problem is relaxed into two subproblems: (i) sensing cost optimization and (ii) networking cost optimization. Both problems are reformulated as combinatorial optimization problems. The sensing cost optimization is shown to have a polynomial order solution. The networking cost optimization is shown to be NP-hard in general, but has a polynomial order solution under specific conditions. A 2-approximation polynomial order relaxation is provided for general networking cost optimization, which is applicable in large-scale system monitoring.