Volume 22, Issue 2 (June 2026)                   IJEEE 2026, 22(2): 3907-3907 | Back to browse issues page

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M S, M S, A I H. Design and Analysis of a Minkowski Fractal Slot-Integrated UWB Antipodal Vivaldi Antenna for Brain Stroke Detection. IJEEE 2026; 22 (2) :3907-3907
URL: http://ijeee.iust.ac.ir/article-1-3907-en.html
Design and Analysis of a Minkowski Fractal Slot-Integrated UWB Antipodal Vivaldi Antenna for Brain Stroke Detection
Sowmya M , Sumi M , Harikrishnan A I
Abstract:   (568 Views)
This article presents the design and optimization of a Minkowski fractal slot-integrated antipodal Vivaldi antenna (MFS-AVA) for brain stroke detection. The antenna is proposed on a 65 × 65 × 1.6 mm³ FR-4 substrate and integrates a tapered slot radiator with a microstrip feed. Key parameters are optimized through parametric analysis. The exponential curve of the radiator arms and edge conductor is fine-tuned for improved bandwidth and impedance matching, while Minkowski fractal slots enhance the reflection coefficient, gain, and directivity. Simulated using CST Studio Suite 2016, the antenna attains an extensive bandwidth spanning from 1.23 GHz to 12 GHz, a maximum gain of 9 dBi, and a radiation efficiency of 87%. The radiation pattern exhibits a directional beam with minimal side lobes, making it suitable for focused microwave imaging. Compared to a conventional design, the MFS-AVA shows improved S11, VSWR, and surface current performance. Its effectiveness is validated using a four-layered tissue-mimicking cylindrical human head model, confirming adequate field penetration and compliance with safety standards. These results demonstrate the proposed antenna’s suitability for UWB microwave imaging in brain stroke detection.
Keywords: antipodal Vivaldi antenna, brain stroke detection, Minkowski fractal slot, tissue-mimicking head model, UWB microwave imaging.
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Type of Study: Research Paper | Subject: Antenna
Received: 2025/05/09 | Revised: 2026/02/01 | Accepted: 2025/10/18
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.