A Channel Calibration Method Based on Weighted Backprojection Algorithm for Multichannel SAR Imaging

Liang, Da; Murphy, Robert W.; Deng, Yunkai; Fan, Huaitao; Zhang, Heng; Zhang, Lei; Wang, Wei; Zhou, Yashi

doi:10.1109/lgrs.2019.2894731

Cited by 15 publications

(4 citation statements)

References 20 publications

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“…where k is the pulse index and PRT is the pulse repetition period. After multichannel signal reconstruction, azimuth imaging methods for traditional SAR can be utilized, such as range-Doppler [29] and BP [30,31]. For wide-swath imaging, BP has some unique advantages.…”

Section: Reviewmentioning

confidence: 99%

Target-Oriented High-Resolution and Wide-Swath Imaging with an Adaptive Receiving–Processing–Decision Feedback Framework

Zhan

Zhang

et al. 2022

Applied Sciences

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High-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) is a promising technique for applications such as maritime surveillance. In the maritime environment, normally only a few targets such as ships are interested. However, before detecting them, considerable receiving resources and computation time are required to receive the echoes of the whole scene and process them to obtain imaging results. This is a heavy burden for online monitoring on platforms with limited resources. To address these issues, different from the concept of whole-scene-oriented imaging, we propose a target-oriented imaging concept, which is implemented by an adaptive receiving–processing–decision feedback framework with feedback connection. (1) To reduce receiving resource consumption, we propose a two-dimensional adaptive receiving module. It receives sub-band echoes of targets only through dechirping and subaperture decomposition in the range and azimuth directions, respectively. (2) To reduce computation time, we propose a target-oriented processing module. It processes subarea echoes of targets only through parallelly conducting inverse fast Fourier transform (IFFT) and back projection (BP) in the range and azimuth directions, respectively. (3) To allocate resources reasonably, we propose a decision module. It decides the necessary receiving window, bandwidth, and image resolution through constant false alarm rate (CFAR) detection. (4) To allocate resources adaptively, we connect three modules with a closed loop to enable feedback. This enables progressive target imaging and detection from rough to fine. Experimental results verify the feasibility of the proposed framework. Compared with the current one, for a typical scenario, at least 30% of the system’s resources and 99% of computation time are saved.

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Section: Reviewmentioning

confidence: 99%

Target-Oriented High-Resolution and Wide-Swath Imaging with an Adaptive Receiving–Processing–Decision Feedback Framework

Zhan

Zhang

et al. 2022

Applied Sciences

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“…High-resolution and wide-swath (HRWS) imaging has become an important trend for the synthetic aperture radar (SAR) technique [1][2][3][4][5], which is conducive to many fields such as continuous earth surface observation [6], moving target indication [7], and maritime reconnaissance [8]. However, for the traditional single-channel SAR system, low pulse repetition frequency (PRF) is required to obtain a wide swath image, which conflicts with the high RPF that is required in azimuth to avoid ambiguity.…”

Section: Introductionmentioning

confidence: 99%

“…To improve the multichannel reconstruction image quality, numerous amplitude and the phase errors calibration methods have been proposed to calibrate channel errors in the literature [2,4,20,22,23]. A time-domain phase mismatch calibration based on the azimuth cross correlation was proposed [24], which derived the phase mismatches from the phase of the cross-correlation function.…”

Section: Introductionmentioning

confidence: 99%

A Novel Sub-Image Local Area Minimum Entropy Reconstruction Method for HRWS SAR Adaptive Unambiguous Imaging

Zhou

Zhan

et al. 2021

Remote Sensing

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Multichannel high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) is a vital technique for modern remote sensing. As multichannel SAR systems usually face the problem of azimuth nonuniform sampling resulting in azimuth ambiguity, the conventional reconstruction methods are adopted to obtain the uniformly sampled signal. However, various errors, especially amplitude, phase, and baseline errors, always significantly degrade the performance of the reconstruction methods. To solve this problem, in this paper, a novel sub-image local area minimum entropy reconstruction method (SILAMER) is proposed, which has favorable adaptability to the HRWS SAR system with various errors. First, according to the idea of image domain reconstruction, the sub-images are generated by employing the back-projection algorithm. Then, we proposed an estimation algorithm based on sub-image local area minimum entropy to obtain the optimal reconstruction coefficient and the compensation phase, which can greatly improve the estimation efficiency by using a local area of the sub-image as the input for estimation. Finally, the sub-images are weighted by the optimal estimated reconstruction coefficient and calibrated by the compensation phase to obtain the unambiguous reconstruction image. The experimental results verify the effectiveness of the proposed method. Noticeably, the proposed algorithm has two additional advantages, i.e., (1) it can perform well under the condition of low signal-to-noise ratio (SNR), and (2) it is suitable for the curved trajectory SAR reconstruction. The simulations verify these advantages of the proposed method.

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“…There is no redundancy of channels required to estimate the subspaces in the proposed algorithm. Liang et al [20] estimated channel phase errors by maximizing the image intensity. The existing channel error compensation is based on the system characteristic, and the error phase is estimated and compensated according to the relationship between channels.…”

Section: Introductionmentioning

confidence: 99%

Interferometric Phase Error Analysis and Compensation in GNSS-InSAR: A Case Study of Structural Monitoring

et al. 2021

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Global navigation satellite system (GNSS)-based synthetic aperture radar interferometry (InSAR) employs GNSS satellites as transmitters of opportunity and a fixed receiver with two channels, i.e., direct wave and echo, on the ground. The repeat-pass concept is adopted in GNSS-based InSAR to retrieve the deformation of the target area, and it has inherited advantages from the GNSS system, such as a short repeat-pass period and multi-angle retrieval. However, several interferometric phase errors, such as inter-channel and atmospheric errors, are introduced into GNSS-based InSAR, which seriously decreases the accuracy of the retrieved deformation. In this paper, a deformation retrieval algorithm is presented to assess the compensation of the interferometric phase errors in GNSS-based InSAR. Firstly, the topological phase error was eliminated based on accurate digital elevation model (DEM) information from a light detection and ranging (lidar) system. Secondly, the inter-channel phase error was compensated, using direct wave in the echo channel, i.e., a back lobe signal. Finally, by modeling the atmospheric phase, the residual atmospheric phase error was compensated for. This is the first realization of the deformation detection of urban scenes using a GNSS-based system, and the results suggest the effectiveness of the phase error compensation algorithm.

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A Channel Calibration Method Based on Weighted Backprojection Algorithm for Multichannel SAR Imaging

Cited by 15 publications

References 20 publications

Target-Oriented High-Resolution and Wide-Swath Imaging with an Adaptive Receiving–Processing–Decision Feedback Framework

Target-Oriented High-Resolution and Wide-Swath Imaging with an Adaptive Receiving–Processing–Decision Feedback Framework

A Novel Sub-Image Local Area Minimum Entropy Reconstruction Method for HRWS SAR Adaptive Unambiguous Imaging

Interferometric Phase Error Analysis and Compensation in GNSS-InSAR: A Case Study of Structural Monitoring

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