利用海杂波有效探测海上小目标是目前雷达探测领域的热点问题,具有重要的应用价值.鉴于海杂波是一种非线性非平稳性的雷达回波信号,充分发挥整体平均经验模式分解的优势,将海杂波分解为若干个不同尺度的独立分量.通过研究发现有目标时,分解出的前5个分量与未分解前信号的相关系数明显减小,因此提出了一种新的海杂波背景下的目标检测方法.通过实测和模拟的海杂波数据进行训练和测试,研究结果表明,该方法能有效地实现海杂波下目标的探测,性能优于经典时域下、分数阶傅里叶变换域下以及平均经验模式分解后的广义Hurst指数的目标检测方法.%Detecting small targets effectively in sea clutter is a hot topic and has important application val-ue. It is proved that the sea clutter is a kind of nonlinear and non-stationary radar echo signal. Consider-ing the advantages of ensemble empirical mode decomposition,the sea clutter is decomposed into several independent component with different scales. It is found by analysis that the correlation coefficient of the former 5 components reduces obviously. So this paper proposes a new target detection method in sea clutter based on ensemble empirical mode decomposition and correlation coefficient. The training and testing ex-periments using real and simulation data signals are completed by support vector machine(SVM). The re-sults show that the proposed method not only effectively realizes the target detection in the sea clutter but also performs much better than the generalized Hurst exponent detecting method in time domain,fractional Fourier transform domain and after ensemble empirical mode decomposition.
展开▼
