Design, Modeling, and Validation of Curvature-Based Shape-Aware Flexible Phased Arrays
Abstract
In situ knowledge of array geometry enables mechanically flexible phased arrays to recover beam-steering performance under deformation without receiver-side RF feedback. This work presents a comprehensive engineering study of curvature-based shape sensing, combining numerical sampling-density and measurement-noise analysis, physical modeling of sensor response, and experimental shape and RF characterization. A study of 11,000 Bézier curves quantifies reconstruction error versus curvature-sampling density and noise, guiding the selection of nine sensing locations. A physical model relates PCB curvature to strain-gauge output voltage, with predictions compared against calibrated sensor measurements. The sensing system is integrated with an eight-element, 6-GHz flexible array and a low-cost, size-scalable, digitally controlled eight-channel phase-shifting module providing 360° tuning with better than 7-bit effective resolution. Across 12 fixture-conformed shapes, including five previously reported cases, the average reconstruction error is 0.06λ. Three additional air-suspended configurations, not prescribed by analytical curves, show an average positional difference of 0.095λ between curvature-based and image-based estimates. Measured radiation patterns demonstrate broadside correction and steering to ±30°. These results provide quantitative engineering guidance for designing and characterizing curvature-based shape-aware flexible phased arrays.
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BibTeX
@misc{dashevsky2026design,
title = {{Design, Modeling, and Validation of Curvature-Based Shape-Aware Flexible Phased Arrays}},
author = {Yair Dashevsky and Alon Elgarat and Matan Gal-Katziri},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2607.08309},
eprint = {2607.08309},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2607.08309},
}
RIS
TY - UNPB
TI - Design, Modeling, and Validation of Curvature-Based Shape-Aware Flexible Phased Arrays
AU - Yair Dashevsky
AU - Alon Elgarat
AU - Matan Gal-Katziri
PY - 2026
DA - 2026/10/29
PB - arXiv
DO - 10.48550/arxiv.2607.08309
UR - https://arxiv.org/abs/2607.08309
AB - In situ knowledge of array geometry enables mechanically flexible phased arrays to recover beam-steering performance under deformation without receiver-side RF feedback. This work presents a comprehensive engineering study of curvature-based shape sensing, combining numerical sampling-density and measurement-noise analysis, physical modeling of sensor response, and experimental shape and RF characterization. A study of 11,000 Bézier curves quantifies reconstruction error versus curvature-sampling density and noise, guiding the selection of nine sensing locations. A physical model relates PCB curvature to strain-gauge output voltage, with predictions compared against calibrated sensor measurements. The sensing system is integrated with an eight-element, 6-GHz flexible array and a low-cost, size-scalable, digitally controlled eight-channel phase-shifting module providing 360° tuning with better than 7-bit effective resolution. Across 12 fixture-conformed shapes, including five previously reported cases, the average reconstruction error is 0.06λ. Three additional air-suspended configurations, not prescribed by analytical curves, show an average positional difference of 0.095λ between curvature-based and image-based estimates. Measured radiation patterns demonstrate broadside correction and steering to ±30°. These results provide quantitative engineering guidance for designing and characterizing curvature-based shape-aware flexible phased arrays.
ER -