Strategies for Distributed Sensor Selection Using Convex Optimization
Consider the estimation of an unknown parameter vector in a linear measurement model. Centralized sensor selection consists in selecting a set of ks sensor measurements, from a total number of m potential measurements. The performance of the corresponding selection is measured by the volume of an estimation error covariance matrix. In this paper, the authors consider the problem of selecting these sensors in a distributed or decentralized fashion. In particular, they study the case of two leader nodes that perform naive decentralized selections. they demonstrate that this can degrade the performance severely.