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In the inverse synthetic aperture radar imaging field, the increasing demand of characterizing small targets drives researchers to seek a higher resolution. One attractive way to improve the resolution is sparse subband imaging. In this paper, we propose a novel framework for sparse subband imaging. First, the fine imaging of each subband is performed, through which the high-order phase errors between subband data are compensated. Then, the Keystone transform is performed to unify the image scales of subbands, and sparse subband returns are coherently processed. Finally, the cross-range compressed subband data are interpolated based on the autoregressive model and then used to reconstruct the high-resolution range profile (HRRP) via the smoothed $\ell^{0}$ algorithm. In the proposed framework, the cross-range compression, which is performed before HRRP reconstruction, enhances the sparsity of the returns and achieves a considerable SNR gain. Consequently, it paves the way for HRRP reconstruction. Furthermore, the proposed framework needs no filling of the band gap between subbands, and it is robust against the band gap. The real data experimental results demonstrate this framework’s ability to achieve a high-resolution fusion image accurately, even under low SNR conditions. [ABSTRACT FROM AUTHOR]

The Fourier transform-based range Doppler method is commonly used in an inverse synthetic aperture radar. Although it has achieved good success in most scenarios, its performance is determined by the rotational angle, and the cross-range resolution is extremely low in the case of a small rotational angle. In this letter, to improve the cross-range resolution, a novel cross-range compression scheme based on the iterative adaptive approach (IAA) is proposed. In addition to the standard IAA to achieve high resolution, the efficient IAA is introduced to suppress the sidelobes due to noise. Both the simulation and experimental results demonstrate that the proposed method has the advantages of parameter-free, high accuracy, and high efficiency. [ABSTRACT FROM PUBLISHER]