DocumentCode
3604966
Title
Adaptive Sparse Sampling to Estimate Radiation and Scattering Patterns to a Specified Uncertainty with Model-Based Parameter Estimation: Compute patterns using as few as two to four samples per lobe.
Author
Miller, Edmund K.
Author_Institution
Los Alamos Nat. Lab., Lincoln, CA, USA
Volume
57
Issue
4
fYear
2015
Firstpage
103
Lastpage
113
Abstract
Analyzing antennas and scatterers in electromagnetics usually involves evaluating far-field radiation and scattering patterns. For problems involving objects, a few wavelengths to an extent, the computing time needed to evaluate a far field is usually much less than that needed to find the source distribution on that object. As the object size increases, however, the time required to obtain the far field can become significant, especially for a monostatic scattering pattern where a new source distribution occurs for each incidence angle or for the radiation and receiving patterns of large complex objects. This is especially the case if the far field is to be sampled finely enough in angle to ensure that important features of the pattern are not missed.
Keywords
antenna radiation patterns; compressed sensing; electromagnetic wave scattering; parameter estimation; adaptive sparse sampling; antennas radiation pattern estimation; far-field radiation pattern; model-based parameter estimation; monostatic scattering pattern; source distribution; Adaptation models; Apertures; Brain modeling; Computational modeling; Electromagnetic scattering; Frequency modulation; Uncertainty;
fLanguage
English
Journal_Title
Antennas and Propagation Magazine, IEEE
Publisher
ieee
ISSN
1045-9243
Type
jour
DOI
10.1109/MAP.2015.2453920
Filename
7225118
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