An Effective Translational Motion Compensation Approach for High-Resolution ISAR Imaging With Time-Varying Amplitude

Yang, Sheng-Hui; Li, Shiqiang; Fan, Huaitao; Li, Hua

doi:10.1109/lgrs.2023.3296702

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…The CPI is divided into multiple subapertures by varied sampling start method, and the range alignment of the echoes within each subapertures is achieved by the cumulative cross-correlation method. Then, the global range alignment is realized based on the MMSE criterion, and more details about the process can be found in [34]. Finally, the phase alignment is achieved by the energy extraction of prominent points.…”

Section: Experimental Results and Performance Analysismentioning

confidence: 99%

An Effective Space-Borne ISAR High-Resolution Imaging Approach for Satellite On-Orbit Based on Minimum Entropy Optimization

Liu,

Yu,

Yang

et al. 2024

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

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The Space Situational Awareness (SSA) program places great significance on obtaining high-resolution images of satellite in space orbit. By utilizing space-borne inverse synthetic aperture radar (SBISAR) can achieve high-resolution imaging of Observed satellite (OS) on-orbit especially in geosynchronous orbit (GEO). However, the complex and nonuniform relative motion of the OS on-orbit and SBISAR produces 2-D spatial variant phase errors, which has a high-order form during long coherent processing intervals (CPI). Up to now, the imaging problem of SBISAR has not been effectively tackled. In this work, a novel method to compensate for the 2-D spatial variant phase errors for SBISAR imaging based on minimum entropy and quasi-Newton's method is proposed. First, the geometric model that considers the relative motion state of SBISAR and the OS on-orbit is established and the optimal observation time period is determined. Second, we propose the echo signal model for the satellite on-orbit and deduce the specific form of the highorder spatial variant phase errors. Third, based on image entropy (IE), quasi-Newton's method is adopted to obtain the optimal solution for the phase error coefficients. Finally, a new initial estimation method that aims to overcome the local convergence of quasi-Newton's method is proposed. By utilizing the optimal parameters, the well-focused SBISAR image can be achieved. Taking GEO satellite imaging as an example, experiments based on scattering point simulation data verify the effectiveness of the proposed method.

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Section: Experimental Results and Performance Analysismentioning

confidence: 99%

An Effective Space-Borne ISAR High-Resolution Imaging Approach for Satellite On-Orbit Based on Minimum Entropy Optimization

Liu,

Yu,

Yang

et al. 2024

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

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“…The synthetic aperture radar (SAR) plays a significant role in various fields, including land and resources, earthquake, mapping, environment, disaster monitoring, and forestry [1]. Additionally, the inverse synthetic aperture radar (ISAR) is a radar imaging system capable of acquiring high-resolution images of moving targets [2][3][4][5][6][7]. Parameter estimation and motion compensation are key techniques in ISAR imaging [8,9].…”

Section: Introductionmentioning

confidence: 99%

A Multi-Domain Joint Novel Method for ISAR Imaging of Multi-Ship Targets

Zhang,

Xu,

et al. 2023

Remote Sensing

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As a key object on the ocean, regulating civilian and military ship targets more effectively is a very important part of maintaining maritime security. One of the ways to obtain high-resolution images of ship targets is the inverse synthetic aperture radar (ISAR) imaging technique. However, in the actual ISAR imaging process, ship targets in a formation often lead to complicated motion conditions. Due to the close distance between the ship targets, the rough imaging results of the targets cannot be completely separated in the image domain, and the small differences in motion parameters lead to overlapping phenomena in the Doppler history. Therefore, for situations in which ship formation targets with little difference in motion parameters are included in the same radar beam, this paper proposes a multi-domain joint ISAR separation imaging method for multi-ship targets. First, the method performs echo separation using the Hough transform (HT) with the minimum entropy autofocus method in the image domain. Secondly, the time–frequency curve is extracted in the time–frequency domain using the short-time Fourier transform (STFT) for time–frequency analysis, which solves the problem of the ship formation targets being aliased on both echo and Doppler history after range compression and achieves the purpose of separating the echo signals of the sub-ship targets with high accuracy. Eventually, better-focused images of each target are obtained via further motion compensation and precise imaging. Finally, the effectiveness of the proposed method is verified using a simulation and measured data.

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