双基地角时变下的ISAR稀疏孔径自聚焦成像

doi:10.7527/S1000-6893.2018.22059

Abstract

Abstract: To solve the problems of poor resolution of bistatic Inverse Synthetic Aperture Radar (ISAR) imaging with time-varying bistatic angle and image defocus caused by the space-varying phase error in traditional sparse aperture imaging, a high-resolution imaging algorithm integrated with phase error correction is proposed based on Bayesian Compressive Sensing (BCS). First, based on the echo data which have been compensated after motion compensation, a phase compensation term is constructed to compensate the Doppler shift caused by the time-varying bistatic angle. Second, a sparse basis matrix changing with the time-varying bistatic angle is constructed to establish a model for compressive sensing-based bistatic ISAR imaging with sparse apertures. The phase error is then treated as the modeling error in ISAR imaging. It is then assumed that each pixel of the target image follows a Laplace prior and noise follows Gaussian prior. Bayesian inference is used to realize non-ambiguous azimuth imaging integrated with phase error correction iteratively. The simulation results verify the validity and superiority of the proposed algorithm.

Key words: bistatic inverse synthetic aperture radar, time-varying bistatic angle, sparse aperture, autofocusing, Bayesian compressive sensing, Laplace prior

CLC Number:

ZHU Xiaoxiu, HU Wenhua, MA Juntao, GUO Baofeng, XUE Dongfang. ISAR autofocusing imaging with sparse apertures and time-varying bistatic angle[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2018, 39(8): 322059-322059.

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ISAR autofocusing imaging with sparse apertures and time-varying bistatic angle

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