Applications of Statistical Directional Characteristics in Synthetic Aperture Radar Imagery Interpretation

Si Chen; Dong Ya Wang; Jian Yang

doi:10.4028/www.scientific.net/AMM.239-240.1269

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 239-240Applications of Statistical Directional...

Applications of Statistical Directional Characteristics in Synthetic Aperture Radar Imagery Interpretation

Abstract:

The concept of Statistical Directional Characteristics (SDCs) is introduced in this paper. The applications of SDCs in Synthetic Aperture Radar (SAR) imagery interpretation are discussed. Two applications, i.e., target recognition and line detection, are raised to demonstrate the effectiveness of the SDCs-based methods. Both numerical and graphical results are presented. According to the experiment results, the SDCs-based methodology shows advantages both in robustness and in efficiency.

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Periodical:

Applied Mechanics and Materials (Volumes 239-240)

Pages:

1269-1273

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.239-240.1269

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Online since:

December 2012

Authors:

Si Chen, Dong Ya Wang, Jian Yang

Keywords:

Line Detection, Statistical Directional Characteristics (SDCs), Synthetic Aperture Radar (SAR), Target Recognition

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References

[1] V. Riasati, U. Srinivas and V. Monga: SAR automatic target recognition via non-negative matrix approximations. Proceedings of SPIE Vol. 8391 (2012).

DOI: 10.1117/12.919348

Google Scholar

[2] M. Negri, P. Gamba, G. Lisini and F. Tupin: IEEE Transactions on Geoscience and Remote Sensing Vol. 44 (2006), pp.2962-2971.

DOI: 10.1109/tgrs.2006.877289

Google Scholar

[3] H. Skriver: IEEE Transactions on Geoscience and Remote Sensing Vol. 50 (2012), pp.2138-2149.

Google Scholar

[4] H. Chaabouni-Chouayakh and M. Datcu: IEEE Geoscience and Remote Sensing Letters Vol. 7 (2010), pp.78-82.

DOI: 10.1109/lgrs.2009.2020070

Google Scholar

[5] L.M. Novak, G.J. Owirka and C.M. Netishen: Pattern Recognition Vol. 27 (1994), pp.607-617.

DOI: 10.1016/0031-3203(94)90040-x

Google Scholar

[6] A. Katartzis, H. Sahli, V. Pizurica and J. Cornelis: IEEE Transactions on Geoscience and Remote Sensing Vol. 39 (2001), p.2073-(2079).

DOI: 10.1109/36.951102

Google Scholar

[7] S. Chen, J. Yang and X.Q. Song: A new method for target aspect estimation in SAR images. Proceedings of ICMT (2010), pp.1060-1063.

Google Scholar

[8] S. Chen and J. Yang: Information and Electronic Engineering Vol. 9 (2011), pp.133-137. (in Chinese).

Google Scholar

[9] S. Chen, J. Yang and X.Q. Song: Systems Engineering and Electronics Vol. 32 (2010), pp.1868-1874. (in Chinese).

Google Scholar