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Proceedings Paper

Adaptive aircraft detection in high-resolution SAR images
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Paper Abstract

In this paper, a new automatic and adaptive aircraft target detection algorithm in high-resolution airport synthetic aperture radar (SAR) images is proposed. Firstly, region segmentation is used to detect the apron area in the images, which provides the potential area where aircrafts may exist and reduce the search range. Secondly, upon the apron area the pre-segmentation is taken to label the possible target points. Thirdly, the constant false alarm rate (CFAR) detector is improved to cope with multi-target detection situation. The clutter pixels in the sliding detection window will be removed automatically based on pre-segmentation result. As a result, more structural features of the targets are preserved. At last, in order to eliminate the detected false targets and solve the problem that the same target is divided into several disconnected areas, a new joint algorithm based on the area recognition factors and distance cluster is presented. The real airborne SAR image data of some airport is used to verify this target detection algorithm, and the result indicates that this algorithm can detect the aircraft target precisely and decrease the false alarm rate.

Paper Details

Date Published: 26 October 2013
PDF: 8 pages
Proc. SPIE 8918, MIPPR 2013: Automatic Target Recognition and Navigation, 891816 (26 October 2013); doi: 10.1117/12.2031132
Show Author Affiliations
Yihua Tan, Huazhong Univ. of Science and Technology (China)
Dan Wu, Huazhong Univ. of Science and Technology (China)
Yansheng Li, Huazhong Univ. of Science and Technology (China)
Qingyun Li, Huazhong Univ. of Science and Technology (China)
Jinwen Tian, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 8918:
MIPPR 2013: Automatic Target Recognition and Navigation
Tianxu Zhang; Nong Sang, Editor(s)

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