基于Harris角点检测与聚类算法的空间自旋目标干涉三维成像

对空间微动目标进行干涉式成像,需要剔除微动曲线交叉位置的干涉相位值,以确保成像的准确性。针对空间自旋目标窄带雷达干涉三维成像问题,首先利用Harris角点检测与聚类算法对回波时频图像中的角点进行搜索与分类,准确找到散射点微动曲线的交叉位置,然后对交叉位置处的干涉相位信息予以剔除,再利用各散射点的干涉相位信息重构出了两基线方向上的坐标曲线,最后根据目标在空间中的圆轨迹与两基线平面内的椭圆轨迹之间的几何关系,实现对空间自旋目标的干涉三维成像。仿真结果验证了所提方法的有效性。 

3D Interferometric Imaging of Spatial Spinning Targets Based on Harris Corner Detection and Clustering Algorithm#br#

In order to ensure the accuracy of imaging, it is necessary to eliminate the interferometric phases at the intersection of the micro-motion curves. In this paper, three-dimensional (3D) interferometric imaging of space spinning targets in low-resolution radar system was studied. At first, corners on time-frequency images were searched and classified by Harris corner detection and clustering algorithm, and the cross position of micro-motion curves were found accurately. Then, the interferometric phases at the intersecting regions was removed. Next, the effective interferometric phases of each scatterer were used to reconstruct the coordinates in the two baseline directions. Finally, according to the geometric relationship between the circular trajectory of the target in space and the elliptical trajectory in the plane consisting of the two baselines, the 3D interferometric imaging of the spinning target is realized. The simulation results verified the effectiveness of the proposed method.