C 2 MI: A Covariance-Coupling Sparse Recovery Algorithm for Metasurface-Based Microwave Imaging
Antenna Measurement Techniques Association Symposium (AMTA), pp. 1–4
Abstract
In this work, we present$\mathbf{C}^{2}$MI (Covariance-Coupling Microwave Imaging), a second-order statistical formulation that enhances imaging under sparse measurements.$\mathrm{C}^{2}$MI models a second-order forward system,$\text{SL}=\mathrm{M}$, where S comprises upper-triangular elements of covariance matrices from permuted and transformed sensing patterns,$L$is the vectorized upper triangle of the scene covariance matrix, and M contains variances of measurement vectors. We solve this underdetermined system via$\ell_{1}$-regularized optimization with a structural constraint enforcing diagonal dominance: each offdiagonal$L_{i j}$must not exceed its corresponding diagonal terms$L_{i i}$and$L_{j j}$. This reflects the prior that strong inter-location coupling (captured by covariance off-diagonals) occurs only when their variances (diagonals) are high. The result is a sparse, interpretable, and structured estimate of scene covariance. Compared to$\ell_{2}+$total variation (TV) methods, C2 MI accurately reconstructs sparse targets using fewer masks-for instance, recovering 14 active pixels in an$8 \times 8$grid with only 20 frequencysweep masks, versus$28+$for$\ell_{2}+$TV. This improves efficiency, enabling real-time, portable, and low-cost microwave imaging. We validate$\mathbf{C}^{2}$MI in MATLAB simulations with metasurface antenna phase gradient measurements, showing promise for security, biomedical, and non-invasive sensing applications.
Authors 4
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University of Missouri–Kansas City
Affiliation as printed
School of Science and Engineering, University of Missouri-Kansas City,AERIAL Lab,MO,USA
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Affiliation as printed
RWTH Aachen University,Chair of High Frequency Electronics,Aachen,Germany
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Affiliation as printed
RWTH Aachen University,Chair of High Frequency Electronics,Aachen,Germany
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University of Missouri–Kansas City
Affiliation as printed
School of Science and Engineering, University of Missouri-Kansas City,AERIAL Lab,MO,USA
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