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Rotational parameters estimation of maneuvering target in ISAR imaging

Journal of Systems Engineering and Electronics 2010年第1期21卷 41-46页

作者： Wenchen Li Jin Liu Xuesong Wang Shunping Xiao Guoyu Wang 63880 Unit PLA Luoyang 471003 R R. China School of Electronic Science and Engineering National University of Defense Technology Changsha 410073 P. R. China

The rotational parameters estimation of maneuvering target is the key of cross-range scaling of ISAR （inverse synthetic aperture radar）, which can be used in the target feature extraction. The cross-range signal model of rotating target with fixed acceleration is presented and the weighted linear least squares estimation of rotational parameters with fixed velocity or acceleration is proposed via the relationship of cross-range FM （frequency modulation） parameter, scatterers coordinates and rotational parameters. The FM parameter is calculated via RWT （Radon-Wigner transform）. The ISAR imaging and cross-range scaling based on scaled RWT imaging method are implemented after obtaining rotational parameters. The rotational parameters estimation and cross-range scaling are validated by the ISAR processing of experimental radar data, and the method presents good application foreground to the ISAR imaging and scaling of maneuvering target.

关键词： inverse synthetic aperture radar maneuvering target rotational parameters estimation cross-range scaling scaled Radon-Wigner transform imaging.

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Autofocus technique for ISAR imaging of uniformly rotating targets based on the ExCoV method

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Journal of Systems Engineering and Electronics 2017年第2期28卷 267-275页

作者： Chengguang Wu Hongqiang Wang Bin Deng Yuliang Qin Wuge Su Institute of Space Electronic Technology School of Electronic Science and EngineeringNational University of Defense Technology Changsha 410073 China

The inverse synthetic aperture radar (ISAR) imaging can be converted into a sparse reconstruction problem and solved by the l1norm minimization algorithm. The basis matrix in sparse ISAR imaging is usually characterized by the unknown rotation rate of a moving target, thus the rotation rate and the sparse signal should be jointly estimated. Especially due to the imperfect coarse motion compensation, we consider the phase error correction problem in the context of the sparse signal reconstruction. To address this issue, we propose an iterative reweighted method, which jointly estimates the rotation rate, corrects the phase error and reconstructs a high resolution ISAR image. The proposed method gives a gradual and interweaved iterative process to refine the unknown parameters to achieve the best sparse representation for the ISAR signals. Particularly, in ISAR image reconstruction, the l1norm minimization algorithm is sensitive to user parameters. Setting these user parameters are not trivial and the reconstruction performance depends significantly on their choices. Then, we consider an expansion-compression variance-component (ExCoV) based method, which is automatic and demands no prior knowledge about signal-sparsity or measurement-noise levels. Both numerical and electromagnetic data experiments are implemented to show the effectiveness of the proposed method. It is shown that the proposed method can estimate the rotation rate and correct the phase errors simultaneously, and its superior performance is proved in terms of high resolution ISAR image. ? 2017 Beijing Institute of Aerospace Information.

关键词： Error compensation Error correction Errors Image processing Image reconstruction inverse problems inverse synthetic aperture radar Iterative methods Motion compensation Numerical methods Rotation Signal reconstruction synthetic aperture radar

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An Effective Autofocus Algorithm for ISAR Imaging

An Effective Autofocus Algorithm for ISAR Imaging

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1996 CIE International Conference of radar(ICR’96)

作者： Ye Wei Bao Zheng Key Laboratory for radar Signal Processing EE Research InstituteXidian University

ISBN: (纸本)0780329147

＜正＞Motion compensation is a key step in inverse synthetic aperture radar（ISAR）imaging.The paper first sets up the array model for ISAR imaging that clearly demonstrates the principle and possible methods for initial phase error calibration.An effective autofocus method called calibrating source iteration algorithm（CASIA）is then presented to calibrate the initial phase errors.Finally, the real measured ISAR data of flying aircraft are processed to test the performance of CASIA and the imaging results confirm its validity.

关键词： synthetic aperture radar motion estimation radar imaging motion compensation aircraft calibration iterative methods array signal processing error analysis electromagnetic wave scattering inverse problems radar cross-sections radar clutter autofocus algorithm ISAR imaging motion compensation inverse synthetic aperture radar array model initial phase error calibration autofocus method calibrating source iteration algorithm measured ISAR data flying aircraft imaging results radar scattering radar clutter

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