基于局部密度聚类的雷达目标散射中心区域分割

散射中心是描述雷达目标高频散射机理的重要特征，准确提取雷达目标散射中心参数对解析雷达目标有着极其重要的研究意义。为了提高散射中心参数计算速度，通常将整幅SAR图分解为多个包含散射中心的小区域，对每个小区域分别进行特征提取和参数计算。根据雷达目标散射中心的特点，本文提出了一种基于局部密度聚类的雷达目标散射中心区域分割技术。首先，首先对雷达图像进行Frost滤波、LSM图像分割和面积滤波的一系列图像预处理获得目标ROI区域，然后对预处理后的图像利用局部密度聚类算法检测散射中心并进行区域分割。实验中，采用模拟数据和真实数据对本文方法和传统图像分割算法展开数值实验，实验结果验证了本文方法在雷达目标散射中心区域分割的有效性和优越性。

Segmentation of scattering center region of radar targets based on local density clustering

The scattering center is a key feature to describe the high-frequency scattering mechanism of radar targets, so the accurate extraction of the scattering center parameters of radar targets is of great research significance for analyzing radar targets. In order to improve the calculation speed of scattering center parameters, the whole SAR image is usually decomposed into several small regions containing scattering centers, and feature extraction and parameter calculation are performed separately for each small region. According to the characteristics of radar target scattering center, a local density clustering-based radar target scattering center region segmentation technique was proposed in this paper. Based on the new method, a series of image preprocessing of Frost filtering, LSM image segmentation and area filtering are performed on the radar image to obtain the target ROI region, and then the preprocessed image is detected by local density clustering algorithm to detect the scattering center point and perform the region segmentation. In the experiments, simulated and real data are used to carry out numerical experiments on the method of this paper and the traditional image segmentation algorithm, and the experimental results verify the effectiveness and superiority of the method of this paper in segmenting the scattering center region of radar targets.