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提出一种合成孔径雷达(SAR,Synthetic Aperture Radar)图像舰船识别新技术.首先通过将SAR图像逆投影至三维(3-D,Three-Dimensional)目标空间,提取目标空间3-D逆投影散射图(BPSI,Back Projection Scattering Image)来表征观测舰船目标的强散射源三维分布;然后采用物理光学法预测各候选舰船目标的3-D热点散射图(HSPI,Hot Scattering Point Image),进而匹配3-D BPSI与3-D HSPI来识别舰船.为了提高计算效率,采用一种两级分层匹配策略:第1步利用几何特征进行预筛选;少数被选取的候选目标参与第2步的分类判决,同时设计一种便于实现的“模糊”匹配准则,克服了“点对点”准则对计算误差等非理想因素敏感的问题.仿真和实测舰船SAR图像的实验结果,显示了3-D散射特征在目标区分能力和可视化效果方面的优势,证明了该方法的有效性.
This paper proposes a new technology of Synthetic Aperture Radar (SAR) image ship recognition.At first, the target space 3-D back-projection scattering is extracted by backprojecting the SAR image to the 3-D (Three-Dimensional) (BPSI, Back Projection Scattering Image) to characterize the three-dimensional distribution of strong scattering sources of the observed ship targets. Then the physical optics method is used to predict the Hot Scattering Point Image (HSPI) of each candidate ship target. Matching 3-D BPSI and 3-D HSPI to identify ships In order to improve computational efficiency, a two-level hierarchical matching strategy is adopted: Step 1 Pre-screening with geometric features; A few selected candidate targets involved in Step 2 , And designs a kind of easy-to-implement “fuzzy” matching criterion to overcome the problem of “point-to-point” criterion sensitive to non-ideal factors such as calculation error.Experimental results of simulating and measuring the SAR images of ships show that The advantages of 3-D scattering feature in the ability of target discrimination and visualization are proved, which proves the effectiveness of this method.