Title: Aperture‐Synthesis Radar Imaging With Compressive Sensing for Ionospheric Research

Abstract

Abstract Inverse methods involving compressive sensing are tested in the application of two‐dimensional aperture‐synthesis imaging of radar backscatter from field‐aligned plasma density irregularities in the ionosphere. We consider basis pursuit denoising, implemented with the fast iterative shrinkage thresholding algorithm, and orthogonal matching pursuit (OMP) with a wavelet basis in the evaluation. These methods are compared with two more conventional optimization methods rooted in entropy maximization (MaxENT) and adaptive beamforming (linearly constrained minimum variance or often “Capon's Method.”) Synthetic data corresponding to an extended ionospheric radar target are considered. We find that MaxENT outperforms the other methods in terms of its ability to recover imagery of an extended target with broad dynamic range. Fast iterative shrinkage thresholding algorithm performs reasonably well but does not reproduce the full dynamic range of the target. It is also the most computationally expensive of the methods tested. OMP is very fast computationally but prone to a high degree of clutter in this application. We also point out that the formulation of MaxENT used here is very similar to OMP in some respects, the difference being that the former reconstructs the logarithm of the image rather than the image itself from basis vectors extracted from themore » observation matrix. MaxENT could in that regard be considered a form of compressive sensing.« less

Authors:

Hysell, D. L.  ^[1];

• Search DOE PAGES for author "Hysell, D. L."
• Search DOE PAGES for ORCID "0000-0001-7410-7335"

Sharma, P.  ^[2];

• Search DOE PAGES for author "Sharma, P."
• Search DOE PAGES for ORCID "0000-0003-2750-0147"

Urco, M.  ^[3];

• Search DOE PAGES for author "Urco, M."
• Search DOE PAGES for ORCID "0000-0002-8894-3294"

Milla, M. A.  ^[4]

• Search DOE PAGES for author "Milla, M. A."
• Search DOE PAGES for ORCID "0000-0001-9067-863X"

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+ Show Author Affiliations

1. Earth and Atmospheric Sciences Cornell University Ithaca NY USA
2. Electrical and Computer Engineering Cornell University Ithaca NY USA
3. Leibniz Institute for Atmospheric Physics Kuehlungsborn Germany
4. Jicamarca Radio Observatory Lima Peru

Publication Date:

Mon Jun 17 00:00:00 EDT 2019

Sponsoring Org.:

USDOE

OSTI Identifier:

1545904

Resource Type:

Publisher's Accepted Manuscript

Journal Name:

Radio Science

Additional Journal Information:

Journal Name: Radio Science Journal Volume: 54 Journal Issue: 6; Journal ID: ISSN 0048-6604

Publisher:

American Geophysical Union (AGU)

Country of Publication:

United States

Language:

English