Angular Sensing by Highly Reconfigurable Pixel Antennas with Joint Radiating Aperture and Feeding Ports Reconfiguration

2026-01-19

AI Summary

This work proposes a highly reconfigurable pixel antenna (HRPA) to overcome the limitations of conventional pixel antennas, which suffer from fixed feed ports that hinder high-precision three-dimensional angle estimation. For the first time, the HRPA achieves joint reconfigurability of both the radiating aperture and feed ports, thereby breaking the constraint imposed by fixed feeding architectures. By employing RF switches to construct a pixelated structure and integrating a joint aperture-feed codebook design with an optimization approach based on the Cramér-Rao lower bound, the proposed HRPA significantly enhances sensing accuracy. Under identical physical dimensions, the HRPA reduces angular estimation error by more than 50% across the full 3D spherical space compared to traditional uniform planar arrays.

Technology Category

• Intelligent Robots: State Estimation
• Machine Learning: Hardware-aware ML
• Computer Vision: Learning & Optimization for CV

Application Category

• Search and Retrieval-Augmented AI: Agentic search
• Responsible Web: Data and user privacy-enhancing technologies for the Web
• Security and Privacy: Large-scale security measurements

Abstract

Angular sensing capability is realized using highly reconfigurable pixel antenna (HRPA) with joint radiating aperture and feeding ports reconfiguration. Pixel antennas represent a general class of reconfigurable antenna designs in which the radiating surface, regardless of its shape or size, is divided into sub-wavelength elements called pixels. Each pixel is connected to its neighboring elements through radio frequency switches. By controlling pixel connections, the pixel antenna topology can be flexibly adjusted so that the resulting radiation pattern can be reconfigured. However, conventional pixel antennas have only a single, fixed-position feeding port, which is not efficient for angular sensing. Therefore, in this work, we further extend the reconfigurability of pixel antennas by introducing the HRPA, which enables both geometry control of the pixel antenna and switching of its feeding ports. The model of the proposed HRPA, including both circuit and radiation parameters, is derived. A codebook is then defined, consisting of pixel connection states and feeding port positions for each sensing area. Based on this codebook, an efficient optimization approach is developed to minimize the Cram\acute{\mathrm{\mathbf{e}}}r-Rao lower bound (CRLB) and obtain the optimal HRPA geometries for angular sensing within a given area. Numerical results show that the HRPA reduces the angle estimation error by more than 50% across the full three-dimensional sphere when compared with a conventional uniform planar array of the same size. This demonstrates the effectiveness of the proposed approach and highlights the potential of HRPA for integrated sensing and communication systems.

Problem

• angular sensing
• pixel antennas
• feeding ports
• reconfigurable antennas
• angle estimation

Innovation

• Highly Reconfigurable Pixel Antenna
• Joint Aperture and Feeding Reconfiguration
• Angular Sensing
• Cramér-Rao Lower Bound Optimization
• Reconfigurable Antenna