结合字典学习技术的ISAR稀疏成像方法

鉴于稀疏ISAR成像方法的成像质量受到待成像场景的稀疏表示不准确的限制，该文将字典学习(DL)技术引入到ISAR稀疏成像中，以提升目标成像质量。该文给出基于离线DL和在线DL两种ISAR稀疏成像方法。前者通过已有同类目标ISAR图像进行学习，获得更优稀疏表示，后者在成像过程中从现有数据中通过优化获得稀疏表示。仿真和实测ISAR数据成像结果表明，结合离线DL和在线DL的成像方法均可获得比现有方法更优的成像结果，离线DL成像优于在线DL成像，而且前者计算效率优于后者。

Sparse ISAR Imaging Exploiting Dictionary Learning

In view of the imaging quality of sparse ISAR imaging methods is limited by the inaccurate sparse representation of the scene to be imaged, the Dictionary Learning (DL) technique is introduced into ISAR sparse imaging to get better sparse representation of the scene. An off-line DL based imaging method and an on-line DL based imaging method are proposed. The off-line DL imaging method can obtain a better sparse representation via a dictionary learned from the available ISAR images. The on-line DL imaging method can obtain the sparse representation from the data currently considered by jointly optimizing the imaging and DL processes. The results of both simulated and real ISAR data show that the on-line DL imaging method and the off-line dictionary imaging method are both able to better sparsely represent the target scene leading to better imaging results. The off-line DL based imaging method works better than the on-line DL based imaging method with respect to both imaging quality and computational efficiency.