Refocusing and Zoom-In Polar Format Algorithm for Curvilinear Spotlight SAR Imaging on Arbitrary Region of Interest

Hu, Ruizhi; Li, Xiaolong; Yeo, Tat‐Soon; Yang, Yuexiang; Chi, Cheng; Zuo, Feng; Hu, Xianyang; Pi, Yiming

doi:10.1109/tgrs.2019.2917717

Cited by 31 publications

(27 citation statements)

References 32 publications

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“…(2). Therefore, techniques such as Stolt interpolation or NUFFT [26], [27] have been utilized to achieve the transformation from non-uniform wavenumber domain samplings to gridded image data. However, when…”

Section: B Imaging Algorithm For Arbitrary Linear Mimo Array Topologiesmentioning

confidence: 99%

Near-Field 3D SAR Imaging Using a Scanning Linear MIMO Array With Arbitrary Topologies

et al. 2020

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For near-field synthetic aperture radar (SAR) imaging, frequency domain imaging algorithms typically require the array elements to be uniformly arranged to facilitate the application of fast Fourier transform (FFT) operations; this greatly restricts the array types that can be used for practical applications. For arrays with non-uniformly positioned antennas, no general and efficient imaging algorithm is available yet. To address this issue, an effective algorithm for efficient three-dimensional (3D) SAR imaging with arbitrary linear multi-input-multi-output (MIMO) array topologies is proposed. Specifically, non-uniform FFT (NUFFT) technology is utilized to tackle the non-uniform sampling issues in both the spatial and the wavenumber domain. Despite the intuitive idea, to achieve satisfied imaging, some issues are non-trivial and should be carefully addressed. Both simulations and experiments show the superiority of the proposed algorithm on computational complexity while maintain the same high imaging precision compared with the back-projection algorithm (BPA). Moreover, we suggest that the concept of NUFFT-based imaging can also be generalized to other imaging regimes with arbitrary array configurations. INDEX TERMS Radar imaging, multi-input-multi-output, synthetic aperture, array topology, millimeterwave imaging.

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Section: B Imaging Algorithm For Arbitrary Linear Mimo Array Topologiesmentioning

confidence: 99%

Near-Field 3D SAR Imaging Using a Scanning Linear MIMO Array With Arbitrary Topologies

et al. 2020

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“…Especially for high resolution image [11], the DOF cannot satisfy the high resolution large scene WAS-SAR imaging, while the image distortion can be corrected via 2-D image interpolation [19], [22]. To focus the image some methods have been proposed like SVPF [16], [19], [23]- [25] and sub-block imaging [26]- [29]. For SVPF, by applying an appropriate spatially-varying filter to the image that is formed by PFA, the defocus effects induced by phase error can be compensated.…”

Section: Introductionmentioning

confidence: 99%

“…After all sub-block images are formed by PFA, they can be mosaicked to get large scene image without defocus. Refocusing and zoom-in ROI is analyzed by Xin Nie and Ruizhi Hu [27]- [29]. In their research work, the received signal is refocused into the center of ROI and applying 2-D interpolation to correct the distortion and project full image onto the imaging grid of ROI.…”

Section: Introductionmentioning

confidence: 99%

Extended Polar Format Algorithm for Large-Scene High-Resolution WAS-SAR imaging

Chen

Wang

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The polar format algorithm (PFA) is a frequencydomain algorithm with high computational efficiency especially for the high resolution imaging applications in wide angle staring synthetic aperture radar (WAS-SAR). Because of the image distortion and defocus caused by plane wave assumption, the effective imaging scene is limited to a small region which is defined as defocus-negligible region. In this paper, a novel sub-block imaging algorithm which firstly applied to WAS-SAR is proposed. This method combines sub-block imaging and spatially variant post filtering (SVPF) which can not only effectively extend depth of focus (DOF) of PFA but also greatly reduces computational burden. What's more, the method of mosaic image is proposed in this paper which can eliminate discontinuity between adjacent sub-blocks. Firstly, the large scene is segmented into multiple regions along range direction and the size of each region is still larger than that of defocus-negligible region. Secondly, refocusing is implemented by a phase compensation of the already de-chirped signal with the center of sub-blocks respectively and each sub-block image is formed by PFA. Thirdly, the region in each sub-block that exceeds the defocus-negligible region is corrected by SVPF and the image distortion can be corrected by 2-D interpolation. Finally, mosaic image method is applied to get the large-scene image with high quality. The algorithm proposed in this paper is efficient and solve the problems in the process of SAR image mosaic such as dislocation and grey scale differences. The simulated and experimental data results demonstrate the effectiveness and practicability of the proposed algorithm.Index Terms-wide angle staring synthetic aperture radar (WAS-SAR), polar format algorithm (PFA), large scene, high resolution, sub-block imaging, SVPF

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“…SAR is an active radar with its own illumination to image a ground scene of interest with high resolution. Many types of improved SAR systems have emerged in recent years [ 4 , 5 , 6 ]. According to the angle between the radiation direction of the radar and movement direction, SAR systems can be divided into three categories: (1) side-looking SAR, (2) squint-looking SAR and (3) forward-looking or back-looking SAR, as shown in Figure 1 .…”

Section: Introductionmentioning

confidence: 99%

Squinted Airborne Synthetic Aperture Radar Imaging with Unknown Curved Trajectory

Huang

et al. 2020

Sensors

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The imagery of airborne highly squinted synthetic aperture radar (SAR) with curved trajectory is a challenging task due to the translational-variant range cell migration (RCM) and azimuth modulation. However, in most cases of practical application, the curved trajectory cannot be accurately known, which brings greater difficulties to the imaging problem. To accommodate these issues, we propose a novel motion modelling and optimisation based imaging algorithm for the highly squinted SAR with unknown curved trajectory. First, to correct the translational-variant RCM, a coarse-to-fine RCM correction scheme as well as a range perturbation approach is applied. Afterwards, an optimisation model of motion information under the criterion of minimum entropy is built during the azimuth processing by nonlinear chirp scaling (NLCS). Correspondingly, a differential evolution (DE) optimisation strategy is proposed to estimate the motion information in an iterative manner. We empirically compare the proposed algorithms with several state-of-the-art highly squinted curved SAR imaging algorithms. Numerical results show the effectiveness of the proposed method in the case without any prior information of the curved trajectory.

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Refocusing and Zoom-In Polar Format Algorithm for Curvilinear Spotlight SAR Imaging on Arbitrary Region of Interest

Cited by 31 publications

References 32 publications

Near-Field 3D SAR Imaging Using a Scanning Linear MIMO Array With Arbitrary Topologies

Near-Field 3D SAR Imaging Using a Scanning Linear MIMO Array With Arbitrary Topologies

Extended Polar Format Algorithm for Large-Scene High-Resolution WAS-SAR imaging

Squinted Airborne Synthetic Aperture Radar Imaging with Unknown Curved Trajectory

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