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

Qian, Yulei; Zhu, Daiyin

doi:10.3390/electronics8030336

Cited by 14 publications

(6 citation statements)

References 27 publications

(41 reference statements)

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“…By operating the 2D Inverse FT according to Equation (26), the echo data can be transformed into the time domain. Consequently, a well-focused SAR image is obtained as follows:…”

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.…”

Section: Introductionmentioning

confidence: 99%

“…The presented method in [25] utilizes the structural information and matched filter processing to implement imaging under sub-Nyquist sampling. In [26], a novel method is proposed to focus the azimuth missing SAR raw data via segmented recovery. The method in [26] mainly consists of multiplication with a designed reference function in the time domain and subsequent segmented recovery in the two-dimensional frequency domain with Stagewise Orthogonal Matching Pursuit (StOMP) [30].…”

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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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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“…By operating the 2D Inverse FT according to Equation (26), the echo data can be transformed into the time domain. Consequently, a well-focused SAR image is obtained as follows:…”

Section: Range Migration Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Qian

Zhu

2019

Remote Sensing

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“…Synthetic Aperture Radar (SAR) has excellent imaging ability, which can obtain high-resolution image under bad weather conditions. The research on SAR includes imaging, target detection, target recognition, time-frequency analysis, and many other aspects [1][2][3][4][5][6][7][8]. The research on Automatic Target Recognition (ATR) of SAR started around 1990 [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

A Vehicle Target Recognition Algorithm for Wide-Angle SAR Based on Joint Feature Set Matching

Peng

2019

Electronics

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Target recognition is an important area in Synthetic Aperture Radar (SAR) research. Wide-angle Synthetic Aperture Radar (WSAR) has obvious advantages in target imaging resolution. This paper presents a vehicle target recognition algorithm for wide-angle SAR, which is based on joint feature set matching (JFSM). In this algorithm, firstly, the modulus stretch step is added in the imaging process of wide-angle SAR to obtain the thinned image of vehicle contour. Secondly, the gravitational-based speckle reduction algorithm is used to obtain a clearer contour image. Thirdly, the image is rotated to obtain a standard orientation image. Subsequently, the image and projection feature sets are extracted. Finally, the JFSM algorithm, which combines the image and projection sets, is used to identify the vehicle model. Experiments show that the recognition accuracy of the proposed algorithm is up to 85%. The proposed algorithm is demonstrated on the Gotcha WSAR dataset.

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“…Synthetic aperture radar (SAR) has become an indispensable means for remote sensing, which is competent to provide high resolution images and videos for monitoring various targets under any weather condition [1][2][3][4][5][6][7]. With the desire for higher resolution, the future task of spaceborne SAR challenges the development of SAR imaging algorithms [8].…”

Section: Introductionmentioning

confidence: 99%

Focusing of Ultrahigh Resolution Spaceborne Spotlight SAR on Curved Orbit

Qian

Zhu

2019

Electronics

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Aiming to acquire ultrahigh resolution images, algorithms for spaceborne spotlight synthetic aperture radar (SAR) imaging typically confront challenges of curved orbit and azimuth spectral aliasing. In order to conquer these difficulties, a method is proposed in this paper to obtain ultrahigh resolution spaceborne SAR images on a curved orbit, which is composed of the modified RMA (Range Migration Algorithm) and the modified deramping-based approach. The modified RMA is developed to deal with the effect introduced by a curved orbit and the modified deramping-based approach is utilized to handle the problem of azimuth spectral aliasing. In the modified RMA, the polynomial expression of SAR two-dimensional spectrum on a curved orbit is derived with fourth-order azimuth phase history model and series reversion. Then, the singular value decomposition (SVD) is applied to decompose the expression of SAR two-dimensional spectrum numerically in order to acquire coordinates for Stolt interpolation in the scenario of curved orbit. In addition, the modified deramping-based approach is derived by introducing orbital state vectors in order to accommodate the situation of curved orbit in the proposed method. Experiments are implemented on point target simulation in order to verify the effectiveness of the presented method. In experiments, the range and azimuth resolution can achieve 0.15 m and 0.14 m, with focused scene size of 3 km by 3 km.

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

Cited by 14 publications

References 27 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

A Vehicle Target Recognition Algorithm for Wide-Angle SAR Based on Joint Feature Set Matching

Focusing of Ultrahigh Resolution Spaceborne Spotlight SAR on Curved Orbit

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