Parametric sparse representation method for ISAR imaging of rotating targets

Wei Rao; Gang Li; Xiqin Wang; Xiang Gen Xia

doi:10.1109/TAES.2014.120535

Parametric sparse representation method for ISAR imaging of rotating targets

Wei Rao, Gang Li, Xiqin Wang, Xiang Gen Xia

Research output: Contribution to journal › Article › peer-review

64 Citations (Scopus)

Abstract

Based on the linear relationship between the chirp rate of cross-range inverse synthetic aperture radar (ISAR) signal and the slant range, a parametric sparse representation method is proposed for ISAR imaging of rotating targets. The ISAR echo is formulated as a parametric joint-sparse signal and the chirp rates at all range bins are estimated by maximizing the contrast of sparse ISAR image. Comparing with homologous algorithms, the computational complexity of the proposed method is significantly reduced.

Original language	English
Article number	6850191
Pages (from-to)	910-919
Number of pages	10
Journal	IEEE Transactions on Aerospace and Electronic Systems
Volume	50
Issue number	2
DOIs	https://doi.org/10.1109/TAES.2014.120535
Publication status	Published - Apr 2014
Externally published	Yes

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10.1109/TAES.2014.120535

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title = "Parametric sparse representation method for ISAR imaging of rotating targets",

abstract = "Based on the linear relationship between the chirp rate of cross-range inverse synthetic aperture radar (ISAR) signal and the slant range, a parametric sparse representation method is proposed for ISAR imaging of rotating targets. The ISAR echo is formulated as a parametric joint-sparse signal and the chirp rates at all range bins are estimated by maximizing the contrast of sparse ISAR image. Comparing with homologous algorithms, the computational complexity of the proposed method is significantly reduced.",

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AB - Based on the linear relationship between the chirp rate of cross-range inverse synthetic aperture radar (ISAR) signal and the slant range, a parametric sparse representation method is proposed for ISAR imaging of rotating targets. The ISAR echo is formulated as a parametric joint-sparse signal and the chirp rates at all range bins are estimated by maximizing the contrast of sparse ISAR image. Comparing with homologous algorithms, the computational complexity of the proposed method is significantly reduced.

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Parametric sparse representation method for ISAR imaging of rotating targets

Abstract

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