Title :
Multiobjective Design of Linear Antenna Arrays Using Bayesian Inference Framework
Author :
Chung-Yong Chan ; Goggans, Paul M.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Central Florida, Orlando, FL, USA
Abstract :
The Bayesian inference framework for design introduced in Chan and Goggans [“Using Bayesian inference for linear antenna array design,” IEEE Trans. Antennas Propag., vol. 59, no. 9, pp. 3211-3217, Sep. 2011] is applied to design linear antenna arrays capable of realizing multiple radiation patterns while satisfying various design requirements. Many design issues are involved when designing a linear antenna array. This paper focuses on four practical design issues: the need for minimum spacing between two adjacent array elements, limitations in the dynamic range and accuracy of the current amplitudes and phases, the ability to produce multiple desired radiation patterns using a single array, and the ability to maintain a desired radiation pattern over a certain frequency band. We present an implementation of these practical design requirements based on the Bayesian inference framework, together with representative examples. Our results demonstrate the capability and robustness of the Bayesian method in incorporating real-world design requirements into the design of linear antenna arrays.
Keywords :
Bayes methods; antenna radiation patterns; linear antenna arrays; Bayesian inference framework; adjacent array elements; current amplitudes; linear antenna arrays; multiobjective design; multiple radiation patterns; Antenna radiation patterns; Arrays; Bayes methods; Chebyshev approximation; Linear antenna arrays; Phased arrays; Automated multiobjective design; Bayesian data fusion; inference-based design; linear antenna array;
Journal_Title :
Antennas and Propagation, IEEE Transactions on
DOI :
10.1109/TAP.2014.2350521