IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Jan 2021)

Ambiguities Suppression for Azimuth Multichannel SAR Based on <inline-formula><tex-math notation="LaTeX">${L_{2,q}}$</tex-math></inline-formula> Regularization With Application to Gaofen-3 Ultra-Fine Stripmap Mode

  • Mingqian Liu,
  • Bingchen Zhang,
  • Zhongqiu Xu,
  • Yan Zhang,
  • Lihua Zhong,
  • Yirong Wu

DOI
https://doi.org/10.1109/JSTARS.2020.3046366
Journal volume & issue
Vol. 14
pp. 1532 – 1544

Abstract

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The azimuth multichannel synthetic aperture radar (SAR) technology is capable of overcoming the minimum antenna area constraint and achieving high-resolution and wideswath (HRWS) imaging. Generally speaking, the pulse repetition frequency (PRF) of the spaceborne multichannel SAR systems should satisfy the azimuthal uniform sampling condition, but it is sometimes impossible due to the limitation of radar system timing conditions, which is often referred as “coverage diagram.” For the Gaofen-3 system, the PRF of each channel at some beam positions is slightly less than that of uniform sampling in the dual-channel mode, leading to the nonuniform undersampling, hence, resulting the azimuth ambiguities in the recovered images. Although the ambiguous energy in Gaofen-3 images is not high in general, it is still noticeable amid surrounding weak clutters of strong targets. In this article, a novel multichannel SAR imaging method for nonuniform undersampling based on L2,q regularization (0 <; q ≤ 1) is proposed. By analyzing the reasons of azimuth ambiguities in the multichannel SAR system, the imaging model is established with emphasizing the difference from conventional single-channel SAR. Then, we combine the multichannel SAR data processing operators with the group sparsity property to construct the novel imaging method. The group sparsity property is modeled by the 2, q-norm, and the L2,q regularization problem can be solved via sparse group thresholding function. It is shown that the proposed method can efficiently suppress the azimuth ambiguities caused by nonuniform undersampling. Simulations and Gaofen-3 real data experiments are exploited to verify the effectiveness of the proposed method.

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