Super-Resolution ISAR Imaging by Sequential Sparse Recovery

Xia Bai; Yu Zou; Yi Feng; Juan Zhao

doi:10.1109/IGARSS46834.2022.9883499

Super-Resolution ISAR Imaging by Sequential Sparse Recovery

Xia Bai, Yu Zou, Yi Feng, Juan Zhao

School of Information and Electronics

Beijing Institute of Technology

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

Abstract

Inverse synthetic aperture radar (ISAR) imaging needs a long coherent processing interval (CPI) to obtain high cross-range resolution. However, the Doppler frequency is time-varying for a maneuvering target, which will produce blurred ISAR image in a long CPI. In this article, we focus on super-resolution ISAR imaging during an adaptive short CPI by using sequential sparse recovery. To enhance the performance of SSL0, a regularized SSLO (Re-SSLO) and an entropy-based stopping rule are presented. Besides, KT-based MTRC compensation, SVD-based dictionary whitening and rotation correlation-based cross-range scaling are introduced into the processing scheme. The superiority of the proposed method is validated by the experimental results based on simulated data.

Original language	English
Title of host publication	IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2963-2966
Number of pages	4
ISBN (Electronic)	9781665427920
DOIs	https://doi.org/10.1109/IGARSS46834.2022.9883499
Publication status	Published - 2022
Event	2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022 - Kuala Lumpur, Malaysia Duration: 17 Jul 2022 → 22 Jul 2022

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	2022-July

Conference

Conference	2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022
Country/Territory	Malaysia
City	Kuala Lumpur
Period	17/07/22 → 22/07/22

Keywords

Inverse synthetic aperture radar (ISAR)
Sparse recovery (SR)
smoothed L0(SL0)

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10.1109/IGARSS46834.2022.9883499

Cite this

Bai, X., Zou, Y., Feng, Y., & Zhao, J. (2022). Super-Resolution ISAR Imaging by Sequential Sparse Recovery. In IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium (pp. 2963-2966). (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2022-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS46834.2022.9883499

@inproceedings{092f98ad42f342ddac96dfd9687e1b03,

title = "Super-Resolution ISAR Imaging by Sequential Sparse Recovery",

abstract = "Inverse synthetic aperture radar (ISAR) imaging needs a long coherent processing interval (CPI) to obtain high cross-range resolution. However, the Doppler frequency is time-varying for a maneuvering target, which will produce blurred ISAR image in a long CPI. In this article, we focus on super-resolution ISAR imaging during an adaptive short CPI by using sequential sparse recovery. To enhance the performance of SSL0, a regularized SSLO (Re-SSLO) and an entropy-based stopping rule are presented. Besides, KT-based MTRC compensation, SVD-based dictionary whitening and rotation correlation-based cross-range scaling are introduced into the processing scheme. The superiority of the proposed method is validated by the experimental results based on simulated data.",

keywords = "Inverse synthetic aperture radar (ISAR), Sparse recovery (SR), smoothed L0(SL0)",

author = "Xia Bai and Yu Zou and Yi Feng and Juan Zhao",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022 ; Conference date: 17-07-2022 Through 22-07-2022",

year = "2022",

doi = "10.1109/IGARSS46834.2022.9883499",

language = "English",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

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

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booktitle = "IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium",

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Bai, X, Zou, Y, Feng, Y & Zhao, J 2022, Super-Resolution ISAR Imaging by Sequential Sparse Recovery. in IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2022-July, Institute of Electrical and Electronics Engineers Inc., pp. 2963-2966, 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022, Kuala Lumpur, Malaysia, 17/07/22. https://doi.org/10.1109/IGARSS46834.2022.9883499

Super-Resolution ISAR Imaging by Sequential Sparse Recovery. / Bai, Xia; Zou, Yu; Feng, Yi et al.
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. Institute of Electrical and Electronics Engineers Inc., 2022. p. 2963-2966 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2022-July).

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

TY - GEN

T1 - Super-Resolution ISAR Imaging by Sequential Sparse Recovery

AU - Bai, Xia

AU - Zou, Yu

AU - Feng, Yi

AU - Zhao, Juan

PY - 2022

Y1 - 2022

N2 - Inverse synthetic aperture radar (ISAR) imaging needs a long coherent processing interval (CPI) to obtain high cross-range resolution. However, the Doppler frequency is time-varying for a maneuvering target, which will produce blurred ISAR image in a long CPI. In this article, we focus on super-resolution ISAR imaging during an adaptive short CPI by using sequential sparse recovery. To enhance the performance of SSL0, a regularized SSLO (Re-SSLO) and an entropy-based stopping rule are presented. Besides, KT-based MTRC compensation, SVD-based dictionary whitening and rotation correlation-based cross-range scaling are introduced into the processing scheme. The superiority of the proposed method is validated by the experimental results based on simulated data.

AB - Inverse synthetic aperture radar (ISAR) imaging needs a long coherent processing interval (CPI) to obtain high cross-range resolution. However, the Doppler frequency is time-varying for a maneuvering target, which will produce blurred ISAR image in a long CPI. In this article, we focus on super-resolution ISAR imaging during an adaptive short CPI by using sequential sparse recovery. To enhance the performance of SSL0, a regularized SSLO (Re-SSLO) and an entropy-based stopping rule are presented. Besides, KT-based MTRC compensation, SVD-based dictionary whitening and rotation correlation-based cross-range scaling are introduced into the processing scheme. The superiority of the proposed method is validated by the experimental results based on simulated data.

KW - Inverse synthetic aperture radar (ISAR)

KW - Sparse recovery (SR)

KW - smoothed L0(SL0)

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M3 - Conference contribution

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BT - IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium

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T2 - 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022

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ER -

Super-Resolution ISAR Imaging by Sequential Sparse Recovery

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