A compressive sensing-based approach for millimeter-wave imaging compatible with Fourier-based image reconstruction techniques

Amir Masoud Molaei; Rupesh Kumar; Shaoqing Hu; Vasiliki Skouroliakou; Vincent Fusco; Okan Yurduseven

doi:10.23919/IRS54158.2022.9905068

A compressive sensing-based approach for millimeter-wave imaging compatible with Fourier-based image reconstruction techniques

Amir Masoud Molaei, Rupesh Kumar, Shaoqing Hu, Vasiliki Skouroliakou, Vincent Fusco, Okan Yurduseven

School of Electronics, Electrical Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

18 Downloads (Pure)

Abstract

The unique characteristics of the millimeter-wave (mmW) frequency band have led to its widespread use in various fields such as communications, imaging, and wireless sensing. This paper addresses two different mmW imaging structures, monostatic and multistatic, in the face of a sparse spatial sampling scenario. By using compressive sensing theory, a solution for image reconstruction, consistent with fast Fourier-based techniques, is presented with compressed data obtained from monostatic imaging. This solution is then generalized to a multiple-input multiple-output (MIMO) imaging case using a multistatic-to-monostatic conversion. Reconstructed images from numerical and experimental data show the satisfactory performance of the presented approach.

Original language	English
Title of host publication	Proceedings of the 23rd International Radar Symposium, IRS 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	87-91
ISBN (Electronic)	9788395602054, 9788395602047
ISBN (Print)	9781665466301
DOIs	https://doi.org/10.23919/IRS54158.2022.9905068
Publication status	Published - 04 Oct 2022
Event	2022 International Radar Symposium - Gdansk, Poland Duration: 12 Sept 2022 → 14 Sept 2022 https://mrw2022.org/irs/

Publication series

Name	International Radar Symposium Proceedings
ISSN (Print)	2155-5745
ISSN (Electronic)	2155-5753

Conference

Conference	2022 International Radar Symposium
Abbreviated title	IRS 2022
Country/Territory	Poland
City	Gdansk
Period	12/09/2022 → 14/09/2022
Internet address	https://mrw2022.org/irs/

Keywords

antenna
compressive sensing
imaging
radar

Access to Document

10.23919/IRS54158.2022.9905068Licence: Unspecified

A compressive sensing-based approach for millimeter-wave imaging compatible with Fourier-based image reconstruction techniques
Copyright 2022 Warsaw University of Technology. This work is made available online in accordance with the publisher’s policies. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 635 KBLicence: Unspecified

Real-time signal processing algorithms for computational millimetre-wave radars
Skouroliakou, V. (Author), Yurduseven, O. (Supervisor) & Ngo, H. Q. (Supervisor), Jul 2024
Student thesis: Doctoral Thesis › Doctor of Philosophy

Cite this

Molaei, A. M., Kumar, R., Hu, S., Skouroliakou, V., Fusco, V., & Yurduseven, O. (2022). A compressive sensing-based approach for millimeter-wave imaging compatible with Fourier-based image reconstruction techniques. In Proceedings of the 23rd International Radar Symposium, IRS 2022 (pp. 87-91). (International Radar Symposium Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/IRS54158.2022.9905068

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title = "A compressive sensing-based approach for millimeter-wave imaging compatible with Fourier-based image reconstruction techniques",

abstract = "The unique characteristics of the millimeter-wave (mmW) frequency band have led to its widespread use in various fields such as communications, imaging, and wireless sensing. This paper addresses two different mmW imaging structures, monostatic and multistatic, in the face of a sparse spatial sampling scenario. By using compressive sensing theory, a solution for image reconstruction, consistent with fast Fourier-based techniques, is presented with compressed data obtained from monostatic imaging. This solution is then generalized to a multiple-input multiple-output (MIMO) imaging case using a multistatic-to-monostatic conversion. Reconstructed images from numerical and experimental data show the satisfactory performance of the presented approach.",

keywords = "antenna, compressive sensing, imaging, radar",

author = "Molaei, {Amir Masoud} and Rupesh Kumar and Shaoqing Hu and Vasiliki Skouroliakou and Vincent Fusco and Okan Yurduseven",

year = "2022",

month = oct,

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doi = "10.23919/IRS54158.2022.9905068",

language = "English",

isbn = "9781665466301",

series = "International Radar Symposium Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "87--91",

booktitle = "Proceedings of the 23rd International Radar Symposium, IRS 2022",

address = "United States",

note = "2022 International Radar Symposium, IRS 2022 ; Conference date: 12-09-2022 Through 14-09-2022",

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Molaei, AM, Kumar, R, Hu, S, Skouroliakou, V, Fusco, V & Yurduseven, O 2022, A compressive sensing-based approach for millimeter-wave imaging compatible with Fourier-based image reconstruction techniques. in Proceedings of the 23rd International Radar Symposium, IRS 2022. International Radar Symposium Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 87-91, 2022 International Radar Symposium, Gdansk, Poland, 12/09/2022. https://doi.org/10.23919/IRS54158.2022.9905068

A compressive sensing-based approach for millimeter-wave imaging compatible with Fourier-based image reconstruction techniques. / Molaei, Amir Masoud; Kumar, Rupesh; Hu, Shaoqing et al.
Proceedings of the 23rd International Radar Symposium, IRS 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 87-91 (International Radar Symposium Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A compressive sensing-based approach for millimeter-wave imaging compatible with Fourier-based image reconstruction techniques

AU - Molaei, Amir Masoud

AU - Kumar, Rupesh

AU - Hu, Shaoqing

AU - Skouroliakou, Vasiliki

AU - Fusco, Vincent

AU - Yurduseven, Okan

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N2 - The unique characteristics of the millimeter-wave (mmW) frequency band have led to its widespread use in various fields such as communications, imaging, and wireless sensing. This paper addresses two different mmW imaging structures, monostatic and multistatic, in the face of a sparse spatial sampling scenario. By using compressive sensing theory, a solution for image reconstruction, consistent with fast Fourier-based techniques, is presented with compressed data obtained from monostatic imaging. This solution is then generalized to a multiple-input multiple-output (MIMO) imaging case using a multistatic-to-monostatic conversion. Reconstructed images from numerical and experimental data show the satisfactory performance of the presented approach.

AB - The unique characteristics of the millimeter-wave (mmW) frequency band have led to its widespread use in various fields such as communications, imaging, and wireless sensing. This paper addresses two different mmW imaging structures, monostatic and multistatic, in the face of a sparse spatial sampling scenario. By using compressive sensing theory, a solution for image reconstruction, consistent with fast Fourier-based techniques, is presented with compressed data obtained from monostatic imaging. This solution is then generalized to a multiple-input multiple-output (MIMO) imaging case using a multistatic-to-monostatic conversion. Reconstructed images from numerical and experimental data show the satisfactory performance of the presented approach.

KW - antenna

KW - compressive sensing

KW - imaging

KW - radar

U2 - 10.23919/IRS54158.2022.9905068

DO - 10.23919/IRS54158.2022.9905068

M3 - Conference contribution

SN - 9781665466301

T3 - International Radar Symposium Proceedings

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BT - Proceedings of the 23rd International Radar Symposium, IRS 2022

PB - Institute of Electrical and Electronics Engineers Inc.

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Molaei AM, Kumar R, Hu S, Skouroliakou V, Fusco V , Yurduseven O. A compressive sensing-based approach for millimeter-wave imaging compatible with Fourier-based image reconstruction techniques. In Proceedings of the 23rd International Radar Symposium, IRS 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 87-91. (International Radar Symposium Proceedings). doi: 10.23919/IRS54158.2022.9905068

A compressive sensing-based approach for millimeter-wave imaging compatible with Fourier-based image reconstruction techniques

Abstract

Publication series

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Keywords

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Student theses

Real-time signal processing algorithms for computational millimetre-wave radars

Cite this