By Topic

Using Bayesian Inference for Linear Antenna Array Design

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Chung-Yong Chan ; Dept. of Electr. Eng., Univ. of Mississippi, Oxford, MS, USA ; Goggans, P.M.

Based on the observation that design and inference are both generalized inverse problems, we devise a new approach that uses the Bayesian inference framework for the automated design of linear antenna arrays. Compared to the optimization-based techniques that are widely used for automated antenna design, this newly-developed method has a prominent advantage, which is the capability to determine automatically the number of antenna elements required to satisfy design requirements and specifications. Three broadside array design problems, which include the null-controlled pattern, the sector beam pattern, and the Chebyshev pattern, along with an end-fire array design problem, are presented as examples. The obtained results demonstrate the advantages of using the Bayesian inference framework for the design of linear antenna arrays.

Published in:

Antennas and Propagation, IEEE Transactions on  (Volume:59 ,  Issue: 9 )