A BCS-based approach for the synthesis of conformal arrays

An innovative conformal array synthesis approach is proposed which exploits a generalization of the Bayesian Compressive Sampling (BCS) technique. Towards this end, the design problem is mathematically formulated in terms of a Bayesian learning one with sparseness priors. The arising functional is t...

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Bibliographic Details
Published in2013 7th European Conference on Antennas and Propagation (EuCAP) pp. 1084 - 1086
Main Authors Oliveri, G., Carlin, M., Bekele, E. T., Massa, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2013
Subjects
Antenna arrays
Bayes methods
Bayesian Compressive Sampling
Compressed sensing
Conformal Arrays
Optimized production technology
Relevance Vector Machine
Sparse Arrays
Support vector machines
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Summary:An innovative conformal array synthesis approach is proposed which exploits a generalization of the Bayesian Compressive Sampling (BCS) technique. Towards this end, the design problem is mathematically formulated in terms of a Bayesian learning one with sparseness priors. The arising functional is then solved by means of a suitable Relevance Vector Machine (RVM) technique. Numerical results are reported to assess the effectiveness of the proposed approach in the synthesis of conformal sparse arrays.
ISBN:1467321877
9781467321877