In this paper, we consider the problem of sensor selection for parameter estimation with
correlated measurement noise. We seek optimal sensor activations by formulating an …

The present paper proposes a data-driven sensor selection method for a high-dimensional
nondynamical system with strongly correlated measurement noise. The proposed method is …

Optimization of sensor selection has been studied to monitor complex and large-scale
systems with data-driven linear reduced-order modeling. An algorithm for greedy sensor …

In many applications of wireless sensor networks (WSNs), sensor positions are often not
known exactly. The existence of sensor position error (SPE) may significantly impact system …

The selection of the minimum number of sensors within a network to satisfy a certain
estimation performance metric is an interesting problem with a plethora of applications. The …

Radar network has been a hot topic in recent years for the plenty of resources it can use,
especially in tracking applications. A popular problem arises, that is how to improve the …

Detection of a signal under noise is a classical signal processing problem. When monitoring
spatial phenomena under a fixed budget, ie, either physical, economical, or computational …

We study the problem of adaptive sensor management for target tracking, where at every
instant we search for the best sensors to be activated at the next time step. In our problem …

We address the sensor selection problem where linear measurements under correlated
noise are gathered at the selected nodes to estimate the unknown parameter. Since finding …

Detection of a signal under noise is a classical signal processing problem. When monitoring
spatial phenomena under a fixed budget, ie, either physical, economical or computational …