For the problem of attribute scattering center parameter estimation in synthetic aperture radar (SAR) image, a method based on the water wave optimization (WWO) algorithm is proposed. First, the segmentation and decoupling of high-energy regions in SAR image are performed in the image domain to obtain the representation of a single scattering center. Afterwards, based on the parameterized model of the attribute scattering center, an optimization problem is constructed to search for the optimal parameters of the separated single scattering center. In this phase, the WWO algorithm is introduced to optimize the parameters. The algorithm has powerfully global and local searching capabilities and avoids falling into local optimum while ensuring the optimization accuracy. Therefore, the WWO algorithm could ensure the reliability of scattering center parameter estimation. The single scattering center after solution is eliminated from the original image and the residual image is segmented into high-energy regions, so the parameters of the next scattering center are estimated sequentially. Finally, the parameter set of all scattering centers in the input SAR image can be obtained. In the experiments, firstly, the parameter estimation verification is performed based on the SAR images in the MSTAR dataset. The comparison of the parameter estimation results with the original image and the reconstruction based on the estimated parameter set reflect the effectiveness of the proposed method. In addition, the experiment is also conducted using the SAR target recognition algorithms based on the estimated attribute parameters. By comparing the recognition performance with other parameter estimation algorithms under the same conditions, the performance superiority of the proposed method in attribute scattering center parameter estimation is further demonstrated.

中文翻译：

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基于水波优化算法的属性散射中心参数估计

针对合成孔径雷达(SAR)图像中属性散射中心参数估计问题，提出一种基于水波优化(WWO)算法的方法。首先，在图像域中对SAR图像中的高能区域进行分割和解耦，得到单个散射中心的表示。之后，基于属性散射中心的参数化模型，构建优化问题，寻找分离的单个散射中心的最优参数。在这个阶段，引入了 WWO 算法来优化参数。该算法具有强大的全局和局部搜索能力，在保证优化精度的同时避免陷入局部最优。所以，WWO算法可以保证散射中心参数估计的可靠性。从原始图像中剔除求解后的单个散射中心，将残差图像分割为高能区域，依次估计下一个散射中心的参数。最终可以得到输入SAR图像中所有散射中心的参数集。实验中，首先基于MSTAR数据集中的SAR图像进行参数估计验证。参数估计结果与原始图像的对比以及基于估计参数集的重建反映了所提方法的有效性。此外，还利用基于估计属性参数的SAR目标识别算法进行了实验。