Title :
A BCS-based approach for the synthesis of conformal arrays
Author :
Oliveri, G. ; Carlin, M. ; Bekele, Ephrem T. ; Massa, A.
Author_Institution :
DISI, Univ. of Trento, Trento, Italy
Abstract :
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.
Keywords :
antenna arrays; belief networks; compressed sensing; conformal antennas; learning (artificial intelligence); BCS-based approach; Bayesian compressive sampling technique; Bayesian learning; RVM technique; conformal sparse arrays; innovative conformal array synthesis approach; relevance vector machine technique; Antenna arrays; Bayes methods; Compressed sensing; Optimized production technology; Support vector machines; Bayesian Compressive Sampling; Conformal Arrays; Relevance Vector Machine; Sparse Arrays;
Conference_Titel :
Antennas and Propagation (EuCAP), 2013 7th European Conference on
Conference_Location :
Gothenburg
Print_ISBN :
978-1-4673-2187-7
Electronic_ISBN :
978-88-907018-1-8
