J4 ›› 2013, Vol. 40 ›› Issue (3): 50-56.doi: 10.3969/j.issn.1001-2400.2013.03.008

• 研究论文 • 上一篇    下一篇

稀疏孔径ISAR的加权特征向量初相校正法

段佳;张磊;盛佳恋;邢孟道   

  1. (西安电子科技大学 雷达信号处理国家重点实验室,陕西 西安  710071)
  • 收稿日期:2011-12-20 出版日期:2013-06-20 发布日期:2013-07-29
  • 通讯作者: 段佳
  • 作者简介:段佳(1989-),女,西安电子科技大学博士研究生,E-mail: bifiduan119@126.com.
  • 基金资助:

    国家自然科学基金资助项目(61001211)

Weighted eigenvector method for sparse-aperture ISAR  phase error correction

DUAN Jia;ZHANG Lei;SHENG Jialian;XING Mengdao   

  1. (National Key Lab. of Radar Signal Processing, Xidian Univ., Xi'an  710071, China)
  • Received:2011-12-20 Online:2013-06-20 Published:2013-07-29
  • Contact: DUAN Jia

摘要:

在低信噪比条件下,不同距离单元信噪比不同,对信号的贡献存在较大的差异,此时传统的特征向量初相校正法不能取得理想的自聚焦效果.利用加权的思想,通过对不同距离单元按信噪比赋予不同权值,提出了一种加权特征向量初相校正法.该自聚焦方法不仅适用于常规逆合成孔径雷达数据,还可用于均匀稀疏以及块状稀疏、非均匀稀疏等非线性稀疏数据的相干化处理.

关键词: 初相校正, 稀疏, 逆合成孔径雷达

Abstract:

The traditional eigenvector method for autofocus can not obtain ideal results in low-SNR (signal-to-noise ratio) cases, because the contribution of the signal in different range bins to the final signal differs greatly. Thus, a weighted eigenvector method for ISAR(inverse synthetic aperture radar) phase error correction is proposed by adding different weights to each range bin according to its SNR. The method can not only deal with normal ISAR signals, but also can handle evenly under-sampled or block sparse, even unevenly sparse data. Finally, actual data processing results confirm the validity of the proposed algorithm.

Key words: phase error correction, sparseness, inverse synthetic aperture radar