Peak Feature Extraction of Target in SAR Image

Article Preview

Abstract:

Peak feature extraction is an important section in SAR automatic target recognition (ATR). A novel method for peak feature extracting has been proposed, and an extended peak characteristic is given. Directly dealing with the peak model, the feature parameters is extracted by means of weighted least-square fitting using neighborhood information; a detailed error analysis for feature parameters extraction imposed by noise has also been carried out, and an analytic variance expression is given. In the end, some experimentation are done using simulated data, domestic real airborne SAR data and MSTAR data, and the results verify the validity and accuracy of the method.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 926-930)

Pages:

3145-3148

Citation:

Online since:

May 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] L. C. Potter and R. L. Moses: IEEE Trans. on Image Processing, Vol. 6 (1997) No. 1, pp.79-91.

Google Scholar

[2] Warren E. Smith, Theodore Irons, Jay Riordan, Steven Sayre: SPIE Vol. 3721 (1999), pp.450-461.

Google Scholar

[3] Reuven Meth: Target Characterization And Matching In Synthetic Aperture Radar Imagery", Doctor, s dissertation, The University of Maryland, college Park, (1998).

Google Scholar

[4] Jones, GrinnellⅢ: IEEE Transactions on Pattern Analysis and Machine intelligence, Vol. 21 (1999), No. 7, pp.603-613.

Google Scholar

[5] Bhanu B, Jones GⅢ, Ahn S: SPIE, Vol. 3370, 1998, pp.493-507.

Google Scholar

[6] Bhanu B, Jones GⅢ: SPIE, Vol. 3721 (1999), pp.507-551.

Google Scholar

[7] June Ho Yi, Bir Bhanu, Ming Li: Pattern Recognition Letters, Vol. 17 (1996), pp.1191-1198.

DOI: 10.1016/0167-8655(96)00071-2

Google Scholar

[8] By-Her Wang: An Automatic Target Recognition System For SAR Imagery", Doctor, s dissertation, Stanford University, Nov. I997.

Google Scholar

[9] G. Gao, K.F. Ji, G.Y. Kuang, et. al: Signal Processing(CN), Vol. 21 (2005) No. 3, 2005, pp.232-235.

Google Scholar