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2015 Sensor Signal Processing for Defence (SSPD)最新文献

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A Location Scale Based CFAR Detection Framework for FOPEN SAR Images 基于位置尺度的FOPEN SAR图像CFAR检测框架
Pub Date : 2015-07-10 DOI: 10.1109/SSPD.2015.7288497
Marco Liguori, A. Izzo, C. Clemente, C. Galdi, M. di Bisceglie, J. Soraghan
The problem of target detection in a complex clutter environment, with Constant False Alarm Ratio (CFAR), is addressed in this paper. In particular an algorithm for CFAR target detection is applied to the context of FOliage PENetrating (FOPEN) Synthetic Aperture Radar (SAR) imaging. The extreme value distributions family is used to model the data and exploiting the location-scale property of this family of distributions, a multi-model CFAR algorithm is derived. Performance analysis on real data confirms the capability of the developed framework to control the false alarm probability.
研究了具有恒定虚警率的复杂杂波环境下的目标检测问题。特别提出了一种用于叶突(FOPEN)合成孔径雷达(SAR)成像的CFAR目标检测算法。利用极值分布族对数据进行建模,利用极值分布族的位置尺度特性,推导了一种多模型CFAR算法。通过对实际数据的性能分析,验证了所开发框架控制虚警概率的能力。
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引用次数: 2
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2015 Sensor Signal Processing for Defence (SSPD)
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