基于WOA-VMD的低慢小目标杂波抑制

Low,Slow and Small Target Clutter Suppression Based on WOA-VMD

以无人机为代表的低慢小(Low,Slow and Small Targets,LSS)目标的检测在雷达探测中因杂波干扰而面临巨大挑战。为了解决低慢小目标杂波抑制问题,本文提出了一种将鲸鱼优化算法(Whale Optimization Algorithm,WOA)与变分模态分解(Variational Mode Decomposition,VMD)相结合的方法,该算法用WOA优化VMD的分解参数,以实现最佳的模态分离效果,有效分离出目标信号与杂波信号。实验结果表明,WOA-VMD方法在复杂环境下能够显著提升低慢小目标的检测概率,计算简单且误差较小,可以对多个目标以及不同多普勒频率大小的目标进行处理,优于传统的杂波抑制方法。

The detection of Low,Slow and Small Targets(LSS)represented by UAVs faces great challenges in radar detection due to clutter interference.In order to solve the problem of LSS clutter suppression,this paper proposes a method that combines the Whale Optimization Algorithm(WOA)with the Variational Mode Decomposition(VMD),the algorithm optimises the decomposition parameters of the VMD using the WOA,in order to achieve the best modal separation effect,and effectively separate the target signal from the clutter signal.The experimental results show that the WOA-VMD method can significantly improve the detection probability of low-slow-small targets in complex environments.The algorithm is simple and the error is less,and it can be processed for multiple targets and targets with different doppler frequency sizes,which is better than the traditional clutter suppression method.