Super-Resolution Passive ISAR Imaging via the RELAX Algorithm

The super-resolution passive radar image can be obtained by estimation of signal parameter via rotational invariance technique (ESPRIT) method under the condition of small angular rotation. However, the ESPRIT method needs high signal noise ratio (SNR), which may not be satisfied in actual passive radar system. Therefore, a super-resolution passive inverse synthetic aperture radar (ISAR) imaging framework of moving targets using the relaxation (RELAX) algorithm is proposed under the condition of few illuminators of opportunity and small rotation angle with low SNR. During this framework, the RELAX model of passive radar imaging is mathematically established, and then we apply the RELAX algorithm to extract spatial frequencies and amplitudes of different scatterers on the target. Finally, the super-resolution passive ISAR image can be obtained by frequency searching. Comparing with existing super-resolution ESPRIT method, the proposed method can achieve a more robust reconstruction in low SNR case.

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