稀疏孔径ISAR的加权特征向量初相校正法

doi:10.3969/j.issn.1001-2400.2013.03.008

Abstract

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

DUAN Jia;ZHANG Lei;SHENG Jialian;XING Mengdao. Weighted eigenvector method for sparse-aperture ISAR phase error correction[J].J4, 2013, 40(3): 50-56.

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Weighted eigenvector method for sparse-aperture ISAR phase error correction

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