In this paper,a comprehensive overview of radar detection methods for low-altitude targets in maritime environments is presented,focusing on the challenges posed by sea clutter and multipath scattering.The performance...In this paper,a comprehensive overview of radar detection methods for low-altitude targets in maritime environments is presented,focusing on the challenges posed by sea clutter and multipath scattering.The performance of the radar detection methods under sea clutter,multipath,and combined conditions is categorized and summarized,and future research directions are outlined to enhance radar detection performance for low-altitude targets in maritime environments.展开更多
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(Variati...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。展开更多
基金supported by the National Natural Science Foundation of China(62171447)。
文摘In this paper,a comprehensive overview of radar detection methods for low-altitude targets in maritime environments is presented,focusing on the challenges posed by sea clutter and multipath scattering.The performance of the radar detection methods under sea clutter,multipath,and combined conditions is categorized and summarized,and future research directions are outlined to enhance radar detection performance for low-altitude targets in maritime environments.
文摘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。