基于二维本征模态函数的 SAR 图像目标检测

合成孔径雷达（SAR）成像具有其独特的优势，能全天时全天候获取目标区域遥感数据，但是其成像机理复杂，获得的 SAR 图像解译困难。从 SAR 成像回波特点出发，结合二维经验模态分解（BEMD）理论，提出了一种基于二维本征模态函数（BIMF）的 SAR 图像目标检测算法。采用仿真和实际的 SAR 图像数据进行了验证实验，实验结果表明，利用融合的 BIMF 特征分量检测目标，其效果优于直接用原始 SAR 图像进行目标检测，并且对不同信噪比的 SAR图像，具有较强适应能力。

SAR Image Target Detection Based on Two Dimensional Intrinsic Mode Function

Synthetic aperture radar (SAR)imaging has its unique advantages,obtaining remote sensing data of target area under all-time and all-weather,but the imaging mechanism is very complex and the right interpretation of SAR images is rather difficult.From the principle of the SAR echo characteristics, combined with the bidimensional empirical mode decomposition (BEMD)theory,a new SAR image target detection algorithm was proposed,which is based on bidimensional intrinsic mode function (BIMF).The simulation and actual SAR image data were used to test the proposed method,and experimental results show the effect of target detection using the fused BIMF feature components is better than that of the direct detection with original SAR image,and it has strong ability to adapt for different signal to noise ratio SAR image.