Multiobjective Design of Linear Antenna Arrays Using Bayesian Inference Framework
Abbreviated Journal Title
IEEE Trans. Antennas Propag.
Automated multiobjective design; Bayesian data fusion; inference-based; design; linear antenna array; PARTICLE SWARM OPTIMIZATION; UNEQUALLY SPACED ARRAYS; DYNAMIC-RANGE; RATIO; PATTERN; PLANAR; ELECTROMAGNETICS; ALGORITHM; NUMBER; Engineering, Electrical & Electronic; Telecommunications
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.
Ieee Transactions on Antennas and Propagation
"Multiobjective Design of Linear Antenna Arrays Using Bayesian Inference Framework" (2014). Faculty Bibliography 2010s. 5145.