海杂波背景下小目标检测及其运动信息的提取

Dim target detection and motion information extraction with sea clutter background

介绍了在基于Hough变换的检测前跟踪算法检测海杂波背景下的低可观测目标的基础上,将动态规划方法引入其中,从每一条"特征直线"所包含的数据点迹中提取最可能构成目标点迹的数据点的方法.仿真结果表明,将Hough变换与基于动态规划的航迹搜索相结合,能够提高低信噪比条件下的目标检测概率,并能比较准确地提取出目标点迹.然后对提取出来的目标点迹进行Kalman滤波,以估计目标的速度,从而为后续的检测与跟踪提供比较准确的目标信息.

Based on the detection of dim targets using Hough-based TBD algorithm with sea clutter background, dynamic programming is introduced to extract data points possibly belonging to targets from the data sets which corresponding to “feature beelines”. The simulation shows that the combination of Hough transform, and dynamic programming can improve the probability of detection at low signal-to-clutter ratio, and correctly extract data points belonging to targets. Then these extracted data points are passed through Kalman filter in order to estimate the velocity of targets for the subsequent process of detection and tracking.