Cargando…
Spatio-Temporal Field Estimation Using Kriged Kalman Filter (KKF) with Sparsity-Enforcing Sensor Placement
We propose a sensor placement method for spatio-temporal field estimation based on a kriged Kalman filter (KKF) using a network of static or mobile sensors. The developed framework dynamically designs the optimal constellation to place the sensors. We combine the estimation error (for the stationary...
Autores principales: | Roy, Venkat, Simonetto, Andrea, Leus, Geert |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6021959/ https://www.ncbi.nlm.nih.gov/pubmed/29865172 http://dx.doi.org/10.3390/s18061778 |
Ejemplares similares
-
Multivariate Kalman filtering for spatio-temporal processes
por: Ferreira, Guillermo, et al.
Publicado: (2022) -
Soft tissue deformation estimation by spatio-temporal Kalman filter finite element method
por: Yarahmadian, Mehran, et al.
Publicado: (2018) -
Compressed sensing cardiac MRI exploiting spatio-temporal sparsity
por: Zamani, Jafar, et al.
Publicado: (2013) -
A Study about Kalman Filters Applied to Embedded Sensors
por: Valade, Aurélien, et al.
Publicado: (2017) -
Kalman filtering : theory and practice using MATLAB /
por: Grewal, Mohinder S.
Publicado: (2001)