未知强杂波下基于DP-TBD的雷达弱目标检测

实测回波的弱目标检测往往面临复杂杂波环境,如信杂比过低、难以获取信杂比与杂波分布等先验信息,此时基于杂波建模的弱目标检测前跟踪(track-before-detect,TBD)方法会遇到困难。针对上述问题,本文提出一种新的用于未知强杂波实测数据的弱目标检测算法。依据未知分布、边缘环境等特点通过改进的最大值恒虚警进行杂波预处理,通过压缩多普勒-距离二维数据避免多帧积累使杂波在同一分辨单元产生强度叠加,最后在时间-距离空间改进基于动态规划的TBD算法解决多帧联合后杂波在不同距离单元的范围扩展,消除虚警。实验结果表明,本文算法相比常规方法具有更高的检测概率及更低的估计误差。

Detection method for weak target under unknown strong clutter based on DP-TBD

The heterogeneous or complex clutter in real environment is usually encountered by detection of weak target. It may be difficult for track-before-detect (TBD) based on modeling of clutter to detect weak target, when the signal-to-clutter ratio (SCR) is low, or prior information and clutter distribution is difficult to obtain. A new detection algorithm is proposed for real data of unknown strong clutter. The improved greatest of constant false alarm rate (CFAR) is used to preprocess the clutter according to the features of unknown distribution, clutter edge, etc. Then two dimensional data of Doppler-distance is compressed to avoid accumulation of clutter in the same unit after association of multi frame. Finally, the dynamic programming based TBD algorithm is improved in the time-distance space to avoid expansion of clutter in different range units and to eliminate false alarms after jointed multi frame. Experimental results show that the proposed algorithm has higher detection probability and lower estimation error than conventional TBD methods.