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一种经验模式分解下的海杂波小目标检测方法
朱雪瑗,杨勇虎,李颖
0
(大连海事大学 航海学院,辽宁 大连116026;大连东软信息学院 计算机与科学系,辽宁 大连116023)
摘要:
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。
关键词:  合成孔径雷达图像  小目标检测  海杂波  整体平均经验模式分解  相关系数
DOI:
基金项目:国家科技支撑计划项目(2014BAB12B02);中央高校基本科研业务费(3132014302)
A novel small target detection method in sea clutter after empirical mode decomposition
ZHU Xueyuan,YANG Yonghu,LI Ying
()
Abstract:
Detecting small targets effectively in sea clutter is a hot topic and has important application value. It is proved that the sea clutter is a kind of nonlinear and non-stationary radar echo signal. Considering 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 experiments using real and simulation data signals are completed by support vector machine(SVM). The results 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.
Key words:  SAR image  small target detection  sea clutter  ensemble empirical mode decomposition  correlation coefficient
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