Focus Improvement for High-Resolution Highly Squinted SAR Imaging Based on 2-D Spatial-Variant Linear and Quadratic RCMs Correction and Azimuth-Dependent Doppler Equalization

Liu, Dong; Lin, Hui; Liu, Hongqing; Liao, Guisheng; Tan, Xiaoheng

doi:10.1109/jstars.2016.2569561

Cited by 40 publications

(28 citation statements)

References 26 publications

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“…However, the need to measure and add such information to the ancillary data complicates the burden on any motion compensation system. In this cases SAR autofocus algorithms [8,9,10,11,12] are used to solve the problem in a blind mode. SAR autofocusing algorithms are categorized into three types: sub-aperture-based algorithms, prominent point-based algorithm, and metric-based autofocus.…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Approach to SAR Data-Focusing

Guaragnella

D’Orazio

2019

Sensors

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Synthetic Aperture RADAR (SAR) is a radar imaging technique in which the relative motion of the sensor is used to synthesize a very long antenna and obtain high spatial resolution. Several algorithms for SAR data-focusing are well established and used by space agencies. Such algorithms are model-based, i.e., the radiometric and geometric information about the specific sensor must be well known, together with the ancillary data information acquired on board the platform. In the development of low-cost and lightweight SAR sensors, to be used in several application fields, the precise mission parameters and the knowledge of all the specific geometric and radiometric information about the sensor might complicate the hardware and software requirements. Despite SAR data processing being a well-established imaging technique, the proposed algorithm aims to exploit the SAR coherent illumination, demonstrating the possibility of extracting the reference functions, both in range and azimuth directions, when a strong point scatterer (either natural or manmade) is present in the scene. The Singular Value Decomposition is used to exploit the inherent redundancy present in the raw data matrix, and phase unwrapping and polynomial fitting are used to reconstruct clean versions of the reference functions. Fairly focused images on both synthetic and real raw data matrices without the knowledge of mission parameters and ancillary data information can be obtained; as a byproduct, azimuth beam pattern and estimates of a few other parameters have been extracted from the raw data itself. In a previous paper, authors introduced a preliminary work dealing with this problem and able to obtain good-quality images, if compared to the standard processing techniques. In this work, the proposed technique is described, and performance parameters are extracted to compare the proposed approach to RD, showing good adherence of the focused images and pulse responses.

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Section: Introductionmentioning

confidence: 99%

A Data-Driven Approach to SAR Data-Focusing

Guaragnella

D’Orazio

2019

Sensors

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“…However, the need to measure and add such information to the ancillary data complicates the burden on any motion compensation system. In this cases SAR autofocus algorithms ( [11][12] [13][14] [15]) are used to solve the problem in a blind mode. SAR autofocusing algorithms are categorized into three types: sub-aperture-based algorithms, prominent point-based algorithm and metric-based autofocus.…”

Section: Introductionmentioning

confidence: 99%

A Data Driven Approach to SAR Data Focusing

Guaragnella

D’Orazio

2018

Preprint

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Synthetic Aperture RADAR (SAR) is a radar imaging technique in which the relative motion of the sensor is used to synthesize a very long antenna and obtain high spatial resolution. Standard SAR raw data processing techniques assume uniform motion of the satellite (or aerial vehicle) and a fixed antenna beam pointing sideway orthogonally to the motion path, assumed rectilinear. Despite SAR data processing is a well established imaging technology that has become fundamental in several fields and applications, in this paper a novel approach has been used to exploit coherent illumination, demonstrating the possibility of extracting a large part of the ancillary data information from the raw data itself, to be used in the focusing procedure. In this work an effort has been carried out to try to focus the raw SAR complex data matrix without the knowledge of any of the parameters needed in standard focusing procedures as Range Doppler (RD) algorithm, Ω − K algorithm and Chirp Scaling (CS) algorithm. All the literature references regarding the algorithms needed to obtain a precise image from raw data use such parameters that refer both to the SAR system acquisition geometry and its radiometric specific parameters. In [22], authors introduced a preliminary work dealing with this problem and able to obtain, in the presence of a strong point scatterer in the observed scene, good quality images, if compared to the standard processing techniques. In this work the proposed technique is described and performances parameters are extracted to compare the proposed approach to RD.

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“…The squint SAR geometry is also different from the conventional broadside one, which results in the difficulties in focusing precisely. The key problems of processing squint SAR data are the compensations of two-dimensional (2D) spatial-variant range cell migration (RCM), and azimuth-variance of Doppler coefficients [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging

et al. 2017

Sensors

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This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR) data processing. Several nonlinear chirp scaling (NLCS) algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC). However, the azimuth depth of focusing (ADOF) is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS) algorithm that is proposed in this paper uses the method of series reverse (MSR) to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data.

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Focus Improvement for High-Resolution Highly Squinted SAR Imaging Based on 2-D Spatial-Variant Linear and Quadratic RCMs Correction and Azimuth-Dependent Doppler Equalization

Cited by 40 publications

References 26 publications

A Data-Driven Approach to SAR Data-Focusing

A Data-Driven Approach to SAR Data-Focusing

A Data Driven Approach to SAR Data Focusing

Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging

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