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Phase adjustment and isar imaging of maneuvering targets with sparse apertures

机译：具有稀疏孔径的机动目标的相位调整和isar成像

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摘要

A multifunctional radar system can only acquire limited and discontinuous wideband pulses, which form sparse aperture (SA) observations of a target. To carry out radar activities (detection, tracking, and imaging) simultaneously for multiple targets, inverse synthetic aperture radar (ISAR) imaging exploiting these SA data is essential for multifunctional radar. In this paper, we study the phase adjustment and full-aperture (FA) reconstruction for SA-ISAR imaging of maneuvering targets. A modified eigenvector-based autofocus approach is proposed to correct phase errors within SA measurements of maneuvering targets. After phase correction, the FA data are reconstructed from SA measurements via sparse representation under a redundant chirp???Fourier dictionary. An efficient algorithm is developed to solve the sparse decomposition optimization, and ISAR images of the maneuvering target are obtained by adaptive joint time-frequency imaging approaches with the reconstructed data. Both simulated and real data sets are used to confirm the effectiveness of the proposed methods.
机译：多功能雷达系统只能获取有限且不连续的宽带脉冲，这些脉冲形成目标的稀疏孔径（SA）观测值。为了同时针对多个目标执行雷达活动（检测，跟踪和成像），利用这些SA数据的逆合成孔径雷达（ISAR）成像对于多功能雷达至关重要。在本文中，我们研究了机动目标的SA-ISAR成像的相位调整和全光圈（FA）重建。提出了一种改进的基于特征向量的自动聚焦方法，以校正机动目标的SA测量中的相位误差。经过相位校正后，在冗余线性调频傅立叶字典下通过稀疏表示从SA测量中重建FA数据。提出了一种有效的算法来解决稀疏分解的优化问题，并通过自适应联合时频成像方法和重构数据获得了机动目标的ISAR图像。模拟数据集和实际数据集均用于确认所提出方法的有效性。

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