A New Rang-Instantaneous Doppler ISAR Imaging Algorithm

Bao Ping Wang; Chao Sun; Jun Jie Guo

doi:10.4028/www.scientific.net/AEF.6-7.682

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HomeAdvanced Engineering ForumAdvanced Engineering Forum Vols. 6-7A New Rang-Instantaneous Doppler ISAR Imaging...

A New Rang-Instantaneous Doppler ISAR Imaging Algorithm

Abstract:

ISAR imaging algorithm based on sparse representation has the advantages of high resolution, noise suppression and dealing with gapped data effectively. The method is based on the hypothesis that the imaging targets move smoothly. But the movement of ISAR imaging targets is usually of high maneuverability, which results in big phase error after motion compensation. Using the traditional RD imaging algorithm and the imaging algorithm based on sparse representation will make the resultant image fuzzy, and can't even be identified. This paper introduces a new range- instantaneous Doppler imaging algorithm based on sparse representation and time-frequency transform, which can effectively image the maneuvering target. The experimental results validate the feasibility of this approach.

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Periodical:

Advanced Engineering Forum (Volumes 6-7)

Pages:

682-687

DOI:

https://doi.org/10.4028/www.scientific.net/AEF.6-7.682

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Online since:

September 2012

Authors:

Bao Ping Wang, Chao Sun, Jun Jie Guo

Keywords:

ISAR, Sparse Representation, Time-Frequency Basis, Time-Frequency Transform

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References

[1] Z. Bao, G. Y. Wang, L. Luo, Range-Instantaneous Doppler Imaging in ISAR, Acta Electronica Sinica[J], 1998, Vol. 26(12): 79-83.

Google Scholar

[2] S. Samadi, M. Cetin, M.A. Masnadi-Shirazi, Sparse representation-based synthetic aperture radar imaging[J]. IEEE Proc. Radar Sonar Navig., 2011, 5 (2): 182 –193.

DOI: 10.1049/iet-rsn.2009.0235

Google Scholar

[3] K. R. Varshney, M. Çetin, and J. W. Fisher, et al., Sparse Representation in Structured Dictionaries with Application to Synthetic Aperture Radar[J]. IEEE Trans on Signal Processing. 2008, Vol. 56(8): 3548-3561.

DOI: 10.1109/tsp.2008.919392

Google Scholar

[4] Zhang L, Xing M D, and Qui C W, et al. Resolution Enhancement for Inversed Synthetic Aperture Radar Imaging Under Low SNR via Improved Compressive Sensing. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(10): 3824-3838.

DOI: 10.1109/tgrs.2010.2048575

Google Scholar

[5] C. D. Austin, E. Ertin , and R. L. Moses. Sparse Signal Methods for 3-D Radar Imaging[J]. IEEE Journal of Selected Topics in Siganl Processing, JUNE 2011, VOL. 5, NO. 3, 408-423.

DOI: 10.1109/jstsp.2010.2090128

Google Scholar

[6] H. X. Wang, Y. Liang, and M. D. Xing, et al. Sparse Signal Representation-Based Space Debris Imaging[J]. Journal of Astronautics, 2011, Vol. 32, No. 10, 2194-2199.

Google Scholar

[7] V. C. Chen and H. Ling. Time-Frequency Transforms for Radar Imaging and Signal Analysis. Norwood, MA: Artech House, (2002).

Google Scholar