中文摘要：

海杂波背景下的微弱漂浮目标检测是雷达目标检测的热点和难点问题。由于海杂波背景下的微弱漂浮目标的回波能量低和多普勒频率通常位于主杂波区,传统的自适应类相参积累检测方法无法有效检测该类目标。基于特征类的目标检测方法是解决海面漂浮目标检测问题的有效途径。本文首先分别提取四个极化通道的三种时域和频域特征（相对平均振幅、相对多普勒峰高和向量熵）,然后在极化通道维度上进行融合,获得四极化通道融合特征。最后,在三维特征空间中使用快速凸包学习算法来确定海杂波的判决区域,从而完成检测。实测海杂波数据实验验证了新方法的有效性,并表明其具有优良的检测性能。

英文摘要：

The detection of floating small target in sea clutter is a hotspot and difficult problem in radar community. The traditional adaptive coherent integration detection methods cannot detect these targets effectively because of the weak energy and overlapping Doppler domain with clutter. The target detection based on characteristic is an effective method to solve sea floating small target detection problem. In this paper,firstly the time domain and frequency domain characteristics（ the relative average amplitude,the relative Doppler peak height and the relative vector-entropy） are extracted from four different polarization channels. Then they are fused to four-polarization-channels characteristics in polarization dimensionality. Finally the fast convexhull learning algorithm is used to obtain the decision region of sea clutter and detect targets’ returns. The experiments based on real datasets show that the new method is effective and has a good detection performance.