基于图连通密度的海面漂浮小目标检测

海面漂浮小目标由于其能量弱，一直是海面目标检测的重难点。传统基于统计模型的漂浮小目标检测算法借助回波能量进行检测，没有利用数据频域幅度间的关联性，导致检测性能受损。该文借助图的处理方式，首先利用回波数据脉冲间频域幅度的关联性计算连通密度，生成邻接矩阵，接着将邻接矩阵转换为拉普拉斯矩阵，提取拉普拉斯矩阵的最大特征值作为检测特征，提出了一种基于图的连通密度的海面漂浮小目标检测算法。通过对实测的全相参的X波段 (IPIX)雷达数据进行连通密度的分析，发现海杂波构成的图比较稠密，而海面漂浮小目标构成的图比较稀疏，故通过连通密度构成的图可以有效地检测海杂波中的漂浮小目标。进一步地，通过与对比算法实验分析发现，该文所提基于图的连通密度的检测算法检测性能明显优越。

Floating Small Target Detection Based on Graph Connected Density in Sea Surface

Due to the weak energy of the floating small targets, it is hard to be detected in sea surface. Relying on the energy, the traditional detectors based on statistical model inevitable loss the detection performance, regardless of the correlation between the frequency domain amplitudes. Therefore, in the paper, the correlation between the frequency domain amplitudes is considered by using the graph. Firstly, the connected density is calculated by the correlation between the frequency domain amplitudes of the echo pulses. Secondly, an adjacency matrix is generated based on the correlation. Thirdly, the adjacency matrix is converted to a Laplacian matrix. Lastly, the maximum eigenvalue of the Laplacian matrix is extracted as the detection feature. Thus, the detector based on the connected density of the graph is proposed for the floating small targets in sea surface. The analysis of the connected density of the measured Ice multiParameter Imaging X-band(IPIX) radar data shows that the graph composed by the sea clutter is relatively dense, whereas the graph composed by the floating small targets is relatively sparse. Thus, the connected density can effectively distinguish the floating small targets between the sea clutter. Furthermore, the experimental results show that, compared with other algorithms, the detection performance of the proposed connected density of the graph algorithm is obviously superior.