Cognitive Fusion for Target Tracking / by Ioannis Kyriakides
By: Kyriakides, Ioannis, autor
Material type: 
E-bookSeries: (Synthesis Lectures on Algorithms and Software in Engineering, 1938-1735).Publisher: Cham : Springer International Publishing, 2019Edition: 1st edition 2019.Description: 1 recurso en línea (VIII, 57 páginas).ISBN: 9783031015281.Subject: Radar | Redes de sensores inalámbricasOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
|
Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | TK6580 2019 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.01112242 |
Browsing Madrid Digital shelves, Shelving location: Acceso Electrónico (UEM) Close shelf browser (Hides shelf browser)
| TK6578 2012 EB Sparse Representations for Radar with MATLAB Examples | TK6580 2009 EB Advanced Radar Detection Schemes Under Mismatched Signal Models | TK6580 2016 EB Radar Cross Section of Dipole Phased Arrays with Parallel Feed Network | TK6580 2019 EB Cognitive Fusion for Target Tracking | TK6580 2022 EB Theory to Countermeasures Against New Radars | TK6580 .G464 2016 EB Group-target tracking | TK6580 .J536 2016 EB Network Radar Countermeasure Systems : Integrating Radar and Radar Countermeasures |
Introduction -- Cognitive Fusion -- Cognitive Fusion for Target Tracking with Foveal and Radar Nodes -- Conclusions -- Bibliography -- Author's Biography.
The adaptive configuration of nodes in a sensor network has the potential to improve sequential estimation performance by intelligently allocating limited sensor network resources. In addition, the use of heterogeneous sensing nodes provides a diversity of information that also enhances estimation performance. This work reviews cognitive systems and presents a cognitive fusion framework for sequential state estimation using adaptive configuration of heterogeneous sensing nodes and heterogeneous data fusion. This work also provides an application of cognitive fusion to the sequential estimation problem of target tracking using foveal and radar sensors.
There are no comments on this title.