SAR图像局部自适应ACCA-CFAR检测算法
doi: 10.3724/SP.J.1146.2007.01041
ACCA-CFAR Detection with Local Adaptive Threshold
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摘要: 该文在ACCA-CFAR(Automatic Censored Cell Averaging-CFAR)的基础上提出了一种以K分布对SAR图像杂波建模的局部自适应ACCA-CFAR目标检测算法。该算法首先估计局部窗口的K分布参数，然后根据参数确定局部ODV(Ordered Data Variability)门限，进而完成背景像素筛选，最后做出检测判决。文中证明了ODV门限与局部统计模型的参数有关，给出了采用局部自适应门限的理论依据。该文以海面舰船SAR图像为例，证明该算法在海面杂波背景中具有较少的虚警，可以完整地检测出舰船目标，保留更精细的结构特征。
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关键词:
- 合成孔径雷达;舰船检测;K分布;恒虚警率
Abstract: A modified ACCA-CFAR method with local adaptive threshold is proposed for SAR image detection based on ACCA-CFAR in this paper, in which the K-distribution is used to describe the clutter. First the parameter of K-distribution is estimated, secondly, the local ODV (Ordered Data Variability) threshold is determined and the background pixels are selected, finally the detection is made. The paper also proves that the ODV threshold is related with the parameter of the local statistical model. Finally, the algorithm is applied to SAR image of ship, and the result indicates that there are fewer false alarms in the new algorithm, and the whole ship targets are detected with more structure details. -
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