Abstract
In this article, we propose a deep neural network (DNN)- for the radiation pattern synthesis of an antenna. The DNN utilizes the radiation patterns as inputs and the amplitude and phase of the antenna elements as outputs. Consequently, the radiation patterns of the array antenna can be easily obtained from the outputs of the trained DNN, which are amplitude and phase of the antenna elements. However, it is difficult to determine the amplitude and phase of each antenna element from the desired pattern in an environment where inter-element coupling exists. For this purpose, 6,859 radiation pattern samples for a $4 \times 1$ array patch antenna were generated by changing the phases of the antenna elements, and those patterns were leveraged to train the proposed DNN with low complexity. The radiation patterns of the ideal square and triangular array shapes, which are practically infeasible to implement, were used as inputs to the DNN. It was confirmed that the radiation pattern generated from the output signals of the DNN was very similar to the input radiation pattern.
Highlights
The radiation pattern of an array antenna is determined by the amplitude and phase of the signal applied to each antenna element [1]
The main contribution of this paper is to provide a deep learning (DL) methodology that derives and outputs the amplitude and phase of the antenna elements in response to an ideal input radiation pattern
In order to derive the radiation patterns, including the case where coupling exists between the antenna elements, a 4 × 1 array patch antenna with a spacing of 0.28 λ was utilized
Summary
The radiation pattern of an array antenna is determined by the amplitude and phase of the signal applied to each antenna element [1]. It is difficult to determine the signal amplitude and phase for each array elements in order to obtain the desired array radiation pattern. Fourier transform or optimization techniques can be utilized to synthesize the radiation pattern of the array antenna [2,3,4]. These methods cannot be implemented in practice, and the synthesis of even a single radiation pattern requires a considerable amount of computation time. To synthesize different types of radiation patterns for the same antenna structure, the algorithm must be re-operated several times for each pattern, resulting in even longer computation time
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
