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Single-pixel polarimetric direction of arrival estimation using programmable coding metasurface aperture.

The Viet Hoang¹, Vincent Fusco², Muhammad Ali Babar Abbasi²

¹Institute of Electronics, Communications, and Information Technology (ECIT), Queen's University Belfast, Belfast, BT3 9DT, UK. tv.hoang@qub.ac.uk.

Scientific Reports

|December 14, 2021

Summary

This summary is machine-generated.

This study introduces a novel single-pixel polarimetric compressive sensing (CS) method for direction of arrival (DoA) estimation. The technique utilizes a programmable metasurface to accurately determine wave direction and polarization from compressed measurements.

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Area of Science:

Electromagnetics and Wave Propagation
Metamaterials and Metasurfaces
Signal Processing and Estimation Theory

Background:

Traditional Direction of Arrival (DoA) estimation methods often require complex sensor arrays.
Compressive Sensing (CS) offers a framework for reconstructing signals from undersampled measurements.
Polarimetric information provides crucial details about wave characteristics beyond spatial location.

Purpose of the Study:

To develop a single-pixel system for polarimetric Direction of Arrival (DoA) estimation.
To leverage a programmable coding metasurface for efficient spatial encoding and compression.
To demonstrate the retrieval of high-fidelity polarimetric DoA information from compressed data.

Main Methods:

A cavity-backed programmable coding metasurface aperture with dynamically modulated waveform diversity was employed.
Spatially incoherent radiation masks encoded incoming plane waves onto a single channel.
The wave-chaotic metasurface's polarimetric properties were utilized to ensure sensitivity to wave polarization states.

Main Results:

The proposed single-pixel technique successfully retrieved polarimetric DoA information from compressed measurements.
Encoding and compression of far-field incident waves into a single channel yielded high-fidelity results.
The metasurface's structured sparsity of dual-polarized coded metamaterial elements enabled the proof of concept.

Conclusions:

A novel single-pixel polarimetric compressive sensing (CS) approach for DoA estimation is demonstrated.
The integration of programmable metasurfaces enables efficient, high-fidelity polarimetric DoA retrieval.
This method offers a promising alternative to traditional array-based DoA estimation techniques.