Varying Amplitude Vibration Phase Suppression Algorithm in ISAL Imaging

Yin, Huicheng; Guo, Liang; Li, Yachao; Han, Liang; Xing, Mengdao; Zeng, Xiaodong

doi:10.3390/rs14051122

Cited by 3 publications

(1 citation statement)

References 18 publications

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“…The first category requires the presence of isolated strong scattering points in the scene, including the Map Drift (MD) algorithm [13], the Multiple Aperture Map Drift (MAM) [14] algorithm, the Phase Gradient Autofocus (PGA) algorithm [15,16], etc. The second category does not require the presence of isolated strong scattering points in the scene, and is based on the image quality of the autofocus methods, including Phase Adjustment by Contrast Enhancement (PACE) algorithm [17,18], the Minimum Entropy Autofocus (MEA) [19,20] algorithm, the Maximum Image Contrast Autofocus (MICA) [21] algorithm based on coordinate descent optimization, and so on.…”

Section: Introductionmentioning

confidence: 99%

An Airborne Arc Array Synthetic Aperture Radar Vibration Error Compensation Method

Xiao,

Huang,

et al. 2024

Sensors

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Compared to conventional radars, arc array synthetic aperture radar (SAR) enables wide-area observation under ideal conditions. However, helicopters carrying arc array SAR platforms are generally smaller in size and more sensitive to vibration, which has a greater impact on the imaging quality. In this paper, the vibration error of the arc array SAR platform is investigated, and a vibration error model of the arc array SAR platform is established. Based on the study of the vibration error model, a vibration phase estimation and compensation algorithm based on the delayed conjugate multiplication method is proposed. In the first step, distance pulse pressure processing is performed on the echo signal. In the second step, the pulse pressure signals and their delays in the same distance unit are subjected to conjugate multiplication, and the phase of the signal after conjugate multiplication is extracted. The extracted phase is then amplitude- and phase-compensated to estimate the vibration phase. In the third step, the vibration phase is compensated in the azimuthal direction of the distance pulse pressure signal, and the pairwise echo is eliminated, which completes the compensation of the airborne arc array SAR vibration platform.

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Section: Introductionmentioning

confidence: 99%

An Airborne Arc Array Synthetic Aperture Radar Vibration Error Compensation Method

Xiao,

Huang,

et al. 2024

Sensors

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Terahertz ISAR Imaging With Nonrigid Vibration Compensation and Sidelobe Suppression of Space Targets

Yuan,

Chen,

Deng

et al. 2024

IEEE Trans. Geosci. Remote Sensing

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Inverse Synthetic Aperture LiDAR Imaging of Rough Targets under Small Rotation Angles

Xue

Cao

et al. 2022

Remote Sensing

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Inverse synthetic aperture LiDAR (ISAL) breaks through the limitations of the diffraction limit and achieves ultra-long-distance radar imaging with centimeter-level resolution. However, because ISAL obtains a high resolution, it is accompanied by a high sampling rate and a large data volume, and the processing process is complicated, which is not conducive to fast real-time imaging of ISAL targets. At the same time, considering that actual non-cooperative targets cannot obtain full-angle ISAL images during movement, in this paper, the Kirchhoff approximation method based on two-dimensional Fourier transform is used to calculate the scattering echo of the rough surface of the target, and then, the rough surface scattering echo of the target coordinate system is obtained through coordinate transformation. After vector superposition, the scattered echo and ISAL image of the rough target are finally obtained, and then the influence of the rotation angle on the ISAL imaging of the rough plate and the rough target is discussed. It is found that a small rotation angle range can also achieve clear ISAL imaging of rough targets, and the influence of different roughness on the ISAL imaging results of different rough targets under a small rotation angle is analyzed. When the roughness is decreased, the target scattering mainly comes from coherent scattering, and the target edge becomes sharper. As the roughness increases, the image energy distribution becomes more uniform. Theoretical and simulation experiments verify the feasibility of ISAL imaging of rough targets under small rotation angles.

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Varying Amplitude Vibration Phase Suppression Algorithm in ISAL Imaging

Cited by 3 publications

References 18 publications

An Airborne Arc Array Synthetic Aperture Radar Vibration Error Compensation Method

An Airborne Arc Array Synthetic Aperture Radar Vibration Error Compensation Method

Terahertz ISAR Imaging With Nonrigid Vibration Compensation and Sidelobe Suppression of Space Targets

Inverse Synthetic Aperture LiDAR Imaging of Rough Targets under Small Rotation Angles

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