The Impact of Antenna Design on Breast Microwave Imaging
Volume 11, Issue 03, Page No 1–8, 2026
Adv. Sci. Technol. Eng. Syst. J. 11(03), 1–8 (2026);
DOI: 10.25046/aj110301
Keywords: Breast imaging, Antenna design, Microwave radar
Breast microwave sensing (BMS) systems offer a low-cost and efficient alternative to current reast cancer screening methods. However, reported performance varies widely due to differences in system configuration, antenna design, measurement protocols, and image reconstruction techniques. This study evaluates the impact of antenna design on key image quality metrics using a controlled experimental platform. Spatial resolution, signal-to-noise ratio (SNR), signal-to-clutter ratio (SCR), intensity shift invariance, and contrast resolution were assessed using six antennas: a horn, a Vivaldi, and four ultra-wideband (UWB) flexible printed circuit board (PCB) antennas. These antennas were selected to assess the effects of antenna type, beam pattern, gain, and physical size. By isolating antenna characteristics while maintaining all other imaging parameters constant, this work provides a systematic comparison of antenna design factors whose individual contributions have not been clearly established in the existing BMS literature. All measurements were acquired using a single imaging chamber with a consistent frequency range, angular sampling, and delay-and-sum reconstruction technique. While higher gain generally improved image quality for high-contrast targets, the results indicate that the antenna footprint and beam pattern also play significant roles. In particular, small, compact omnidirectional PCB antennas with 6 dBi gain may improve spatial resolution and contrast compared to a horn antenna with 12 dBi gain. Directional antennas exhibited reduced sensitivity, with horn antenna beam patterns affecting contrast and spatial uniformity. These findings highlight the importance of considering multiple antenna design parameters, rather than only gain, when optimizing BMS systems for robust, portable deployment in low-income and remote regions.
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