Computational polarimetric microwave imaging

TL;DR

This paper introduces a novel computational polarimetric microwave imaging method using a frequency-diverse metasurface, enabling high-resolution imaging with simplified hardware and enhanced target information retrieval.

Contribution

It develops a new theoretical framework for computational polarimetric imaging and demonstrates experimental validation, extending scalar models to tensor susceptibility estimation.

Findings

High-resolution polarimetric imaging achieved with a single transceiver.

Theoretical framework extended to recover susceptibility tensors.

Experimental validation confirms the approach's effectiveness.

Abstract

We propose a polarimetric microwave imaging technique that exploits recent advances in computational imaging. We utilize a frequency-diverse cavity-backed metasurface, allowing us to demonstrate high-resolution polarimetric imaging using a single transceiver and frequency sweep over the operational microwave bandwidth. The frequency-diverse metasurface imager greatly simplifies the system architecture compared with active arrays and other conventional microwave imaging approaches. We further develop the theoretical framework for computational polarimetric imaging and validate the approach experimentally using a multi-modal leaky cavity. The scalar approximation for the interaction between the radiated waves and the target---often applied in microwave computational imaging schemes---is thus extended to retrieve the susceptibility tensors, and hence providing additional information about the targets. Computational polarimetry has relevance for existing systems in the field that extract polarimetric imagery, and particular for ground observation. A growing number of short-range microwave imaging applications can also notably benefit from computational polarimetry, particularly for imaging objects that are difficult to reconstruct when assuming scalar estimations.