SAR图像舰船识别的三维空间逆投影与匹配技术

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.

3-D back projection and matching for ship recognition from SAR images

A new technique for ship recognition from synthetic aperture radar (SAR) images was proposed. First, a method of projecting SAR image back to the three-dimensional (3-D) target space was developed to obtain the 3-D distribution of the observed target scatterers, namely the 3-D back projection scattering image (BPSI). Next, the 3-D hot scattering point images (HSPIs) of candidate ships as the benchmark were predicted via the physical optics (PO) method. To classify the observed ship efficiently, a two-stage matching scheme was applied: the first stage using geometric features implemented a pre-selection to reduce the number of candidate models from the classification library; the resulting models would undergo the subsequent recognition stage, where a fuzzy matching between the 3-D BPSI and 3-D HSPI was carried out easily and also less sensitive to nonideal factors such as calculation errors than point to point matching. Experimental results for simulated and real ship SAR images display the high discrimination and better visual effect of the 3-D scattering feature, and demonstrate the effectiveness of the proposed approach.