TY - JOUR
T1 - Microwave Integrated Sensing and Imaging Using Reconfigurable Metacavity
AU - Zhao, Mengran
AU - Wang, Luyi
AU - Zhu, Shitao
AU - Chen, Xiaoming
AU - Yurduseven, Okan
N1 - Publisher Copyright:
© 2025 IEEE. All rights reserved, including rights for text and data mining, and training of artificial intelligence and similar technologies.
PY - 2025
Y1 - 2025
N2 - The rapid development of Internet of Things (IoT) has sparked significant demand for target localization and recognition. In this article, we propose a new hardware solution—reconfigurable metacavity (RM)—to enable the realization of microwave integrated sensing and imaging (ISAI). The proposed RM features an electrically oversized metacavity, with its back wall replaced by a reconfigurable metasurface and its top surface etched with leaky cross-shaped irises. By electronically tuning each constitutive element of the reconfigurable metasurface, the RM can generate low-correlated chaotic wavefronts to form a sensing matrix, thereby facilitating the realization of compressive sensing (CS)-based direction-of-arrival (DoA) estimation and computational imaging (CI) using the same hardware architecture. The proposed RM enables a single-channel configuration that achieves physical layer compression through its sensing matrix, offering a complexity-reduced, energy-efficient, and cost-effective solution for ISAI applications.
AB - The rapid development of Internet of Things (IoT) has sparked significant demand for target localization and recognition. In this article, we propose a new hardware solution—reconfigurable metacavity (RM)—to enable the realization of microwave integrated sensing and imaging (ISAI). The proposed RM features an electrically oversized metacavity, with its back wall replaced by a reconfigurable metasurface and its top surface etched with leaky cross-shaped irises. By electronically tuning each constitutive element of the reconfigurable metasurface, the RM can generate low-correlated chaotic wavefronts to form a sensing matrix, thereby facilitating the realization of compressive sensing (CS)-based direction-of-arrival (DoA) estimation and computational imaging (CI) using the same hardware architecture. The proposed RM enables a single-channel configuration that achieves physical layer compression through its sensing matrix, offering a complexity-reduced, energy-efficient, and cost-effective solution for ISAI applications.
KW - Computational imaging (CI)
KW - direction-of-arrival (DoA)
KW - metacavity
KW - reconfigurable metasurface
UR - https://www.scopus.com/pages/publications/105001514219
U2 - 10.1109/TMTT.2025.3552130
DO - 10.1109/TMTT.2025.3552130
M3 - 文章
AN - SCOPUS:105001514219
SN - 0018-9480
VL - 73
SP - 5592
EP - 5606
JO - IEEE Transactions on Microwave Theory and Techniques
JF - IEEE Transactions on Microwave Theory and Techniques
IS - 8
ER -