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针对实测海杂波数据信号进行分析,判定海杂波信号具有多重分形的特性.鉴于海杂波是一种非线性非平稳性的雷达回波信号,充分发挥经验模式分解(EMD)的优势,并结合多重分形的特性,提出一种新的海杂波背景下的目标检测方法.首先,使用EMD方法将海杂波信号分解为若干个固有模态函数分量(IMF);然后,利用多重分形趋势起伏分析法(MF-DFA)求主IMF分量的广义Hurst指数;最后,通过实测的海杂波数据进行训练和测试.研究结果表明,该方法可有效实现海杂波下的目标探测,且性能优于经典时域和分数阶傅里叶变换(FRFT)域下的广义Hurst指数的目标检测方法.
According to the measured sea clutter data signals, it is judged that the sea clutter signals have multifractal characteristics.While the sea clutter is a kind of non-linear and non-stationary radar echoes, it gives full play to the advantages of empirical mode decomposition (EMD) Combining with the characteristics of multifractal, this paper proposes a new target detection method in the background of sea clutter.Firstly, the EMD method is used to decompose the sea clutter signal into several intrinsic mode function components (IMFs). Then, The trend analysis (MF-DFA) is used to find the generalized Hurst index of the IMF component. Finally, the real-time sea clutter data are used to train and test the results. The results show that this method can effectively achieve the target detection under sea clutter The target detection method is superior to the generalized Hurst index in classical time domain and fractional Fourier transform (FRFT) domain.