SUPER-RESOLUTION ISAR IMAGING BY SEQUENTIAL SPARSE RECOVERY

被引：0

作者：

Bai, Xia ^{[1
]}

Zou, Yu ^{[1
]}

Feng, Yi ^{[1
]}

Zhao, Juan ^{[1
]}

机构：

[1] Beijing Inst Technol, Sch Informat & Elect, Beijing 100081, Peoples R China

来源：

2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年

基金：

中国国家自然科学基金;

关键词：

Inverse synthetic aperture radar (ISAR); Sparse recovery (SR); smoothed L0(SL0);

D O I：

10.1109/IGARSS46834.2022.9883499

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Inverse synthetic aperture radar (ISAR) imaging needs a long coherent processing interval (CPI) to obtain high cross-range resolution. However, the Doppler frequency is time-varying for a maneuvering target, which will produce blurred ISAR image in a long CPI. In this article, we focus on super-resolution ISAR imaging during an adaptive short CPI by using sequential sparse recovery. To enhance the performance of SSL0, a regularized SSL0 (Re-SSL0) and an entropy-based stopping rule are presented. Besides, KT-based MTRC compensation, SVD-based dictionary whitening and rotation correlation-based cross-range scaling are introduced into the processing scheme. The superiority of the proposed method is validated by the experimental results based on simulated data.

引用

页码：2963 / 2966

页数：4

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