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 …
W Ma, X Dang, Q Cheng, H Zhu - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 …
X Li, T Zhang, W Yi, L Kong, X Yang - IEEE Sensors Journal, 2019 - ieeexplore.ieee.org
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 …
YH Kim - EURASIP Journal on Advances in Signal Processing, 2024 - Springer
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 …