摘要
针对SAR(synthetic aperture radar)ATR(auto target recognition)算法中的ROI(region of interest)提取通常由一个CFAR(constant false alarm rate)检测器和聚类算法来完成,该方法在高波段SAR目标检测中具有优良的性能,而在UWB SAR(ultra-wide band synthetic aperture radar)叶簇遮蔽目标检测中效果不佳。提出了一种适于叶簇遮蔽目标检测的ROI提取方法,该方法由小滑窗中值滤波、低门限CFAR检测、形态学操作和聚类算法四部分组成,能够在叶簇遮蔽目标检测中很好地完成ROI提取,基于实际UWB SAR图像的ROI提取结果验证了该方法的有效性。
ROI （region of interest） extract in SAR （synthetic aperture radar） ATR （auto target recognition） algorithm is usually accomplished by a CFAR （Constant False Alarm rate） detector followed by a clustering algorithm. It has an excellent performance on target detection in high frequency SAR images. But it isn＇t effective to extract ROI when it is used to detect foliage-concealed targets in UWB SAR images. So a ROI extract method is proposed for the foliage-concealed target detection. The proposed method is composed of a median filter of small window; a CFAR detector of low threshold; a morphologic operation and a clustering algorithm. It is effective to complete ROI extract in the foliage-concealed target detection. The ROI extract results of different extract methods based on a factual UWB SAR image testify the efficiency of the proposed method.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2007年第11期1837-1841,共5页
Systems Engineering and Electronics
基金
国家自然科学基金资助课题(60402034)
