Super-Resolution Sparse Aperture ISAR Imaging of Maneuvering Target via the RELAX Algorithm

Wang, Yong; Liu, Qiuchen

doi:10.1109/jsen.2018.2868308

Cited by 24 publications

(15 citation statements)

References 34 publications

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“…Complex deconvolution is implemented by seeking the solution for Equation (18). After estimating S c (τ,f η ), the recovery of the 2D spectrum of the raw data can be obtained with Equation (22). As the 2D spectrum of raw data is recovered, the focused image can be acquired via recovered data focusing.…”

Section: Range Migration Algorithmmentioning

confidence: 99%

“…Additionally, as missing or gapped data can be regarded as sparse sampling data, the sparse optimization method can also be implemented on sparse SAR and Inverse SAR (ISAR) data [22][23][24][25][26]. In [22], a novel ISAR imaging algorithm with a relaxation technique is proposed to focus azimuth Nevertheless, conventional SAR imaging algorithms usually perform unsatisfactorily in focusing periodically gapped raw SAR data. Therefore, novel methods are expected to be developed to obtain focused images from periodically gapped raw SAR data.…”

Section: Introductionmentioning

confidence: 99%

“…In [22], a novel ISAR imaging algorithm with a relaxation technique is proposed to focus azimuth randomly sparse ISAR data. The proposed method in [22] is capable of obtaining high quality images from partially available ISAR data. In [23], a new method is proposed to deal with azimuth periodically gapped SAR raw data.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Image Formation of Azimuth Periodically Gapped SAR Raw Data with Complex Deconvolution

Qian

Zhu

2019

Remote Sensing

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The phenomenon of periodical gapping in Synthetic Aperture Radar (SAR), which is induced in various ways, creates challenges in focusing raw SAR data. To handle this problem, a novel method is proposed in this paper. Complex deconvolution is utilized to restore the azimuth spectrum of complete data from the gapped raw data in the proposed method. In other words, a new approach is provided by the proposed method to cope with periodically gapped raw SAR data via complex deconvolution. The proposed method provides a robust implementation of deconvolution for processing azimuth gapped raw data. The proposed method mainly consists of phase compensation and recovering the azimuth spectrum of raw data with complex deconvolution. The gapped data become sparser in the range of the Doppler domain after phase compensation. Then, it is feasible to recover the azimuth spectrum of the complete data from gapped raw data via complex deconvolution in the Doppler domain. Afterwards, the traditional SAR imaging algorithm is capable of focusing the reconstructed raw data in this paper. The effectiveness of the proposed method was validated via point target simulation and surface target simulation. Moreover, real SAR data were utilized to further demonstrate the validity of the proposed method.

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Section: Range Migration Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Image Formation of Azimuth Periodically Gapped SAR Raw Data with Complex Deconvolution

Qian

Zhu

2019

Remote Sensing

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“…In addition to spectral analysis methods, the sparse optimization can be also utilized to deal with missing SAR or ISAR data [17][18][19][20]. In [17], a novel centralized sparse representation based SAR imaging method is proposed to deal with sparse sampling SAR data.…”

Section: Introductionmentioning

confidence: 99%

“…In [19], a method is proposed to cope with azimuth periodically gapped raw data with greedy method. In [20], a novel super resolution imaging algorithm with relaxation technique for sparse aperture ISAR (Inverse SAR) is presented. Sparse optimization is capable of improving imaging quality on missing data and is usually functioned as recovering the complete data in a certain domain.…”

Section: Introductionmentioning

confidence: 99%

High Resolution Imaging from Azimuth Missing SAR Raw Data via Segmented Recovery

Qian

Zhu

2019

Electronics

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Synthetic Aperture Radar (SAR) raw data missing occurs when radar is interrupted by various influences. In order to cope with this problem, a new method is proposed to focus the azimuth missing SAR raw data via segmented recovery in this paper. A reference function in time domain is designed to make the missing raw data sparser in two dimensional frequency domain. Afterwards, greedy algorithms are available to recover the missing data in two dimensional frequency domain. In addition, in order to avoid range frequency aliasing problem caused by reference function multiplication in time domain, the missing raw data is split into several parts in range direction and is recovered with a segmented recovery strategy. Then, the recovered raw data is available to be focused with traditional SAR imaging algorithms. The range migration algorithm is chosen to deal with the recovered raw data in this paper. Point target and area target simulations are carried out to validate the effectiveness of the proposed method on azimuth missing SAR raw data. Moreover, the proposed method is implemented on real SAR data in order to further provide convincing demonstration.

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Noise-robust interferometric ISAR imaging of 3-D maneuvering motion targets with fine image registration

et al. 2022

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Super-Resolution Sparse Aperture ISAR Imaging of Maneuvering Target via the RELAX Algorithm

Cited by 24 publications

References 34 publications

Image Formation of Azimuth Periodically Gapped SAR Raw Data with Complex Deconvolution

Image Formation of Azimuth Periodically Gapped SAR Raw Data with Complex Deconvolution

High Resolution Imaging from Azimuth Missing SAR Raw Data via Segmented Recovery

Noise-robust interferometric ISAR imaging of 3-D maneuvering motion targets with fine image registration

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