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Fractal characteristic in frequency domain for target detection within sea clutter

机译:海杂波内目标检测的频域分形特征

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摘要

This study mainly describes the fractal property of the frequency spectrum of the sea clutter and the application of the obtained fractal characteristic in frequency domain to the constant-false-alarm-rate (CFAR) target detection within sea clutter. First, this study takes fractional Brownian motion (FBM) for example, and the spectrum of the FBM is proved to be fractal theoretically on condition that the time series of the FBM is fractal. This argument lays the foundation for the application of fractal theory to the frequency spectrum. Next, X- and S-band real radar data are used for the verification of the fractal property of the real sea clutter frequency spectrum. Finally, the effects of the length of the time series and fast Fourier transform (FFT) are analysed in detail. The results show that the frequency spectrum of the real sea clutter is fractal in the statistical sense and the frequency Hurst exponents of clutter range bins and target range bins are distinguishable. Therefore the frequency Hurst exponent is used for the CFAR target detection within sea clutter.
机译:这项研究主要描述了海杂波频谱的分形特性,以及在频域中获得的分形特征在海杂波内恒虚警率(CFAR)目标检测中的应用。首先,本研究以分数布朗运动(FBM)为例,在FBM时间序列为分形的情况下,从理论上证明了FBM的频谱是分形的。此论点为将分形理论应用于频谱奠定了基础。接下来,使用X波段和S波段真实雷达数据验证真实海杂波频谱的分形特性。最后,详细分析了时间序列长度和快速傅立叶变换(FFT)的影响。结果表明,实际海杂波的频谱在统计意义上是分形的,杂波距离箱和目标距离箱的频率赫斯特指数是可区分的。因此,赫斯特频率指数用于海杂波内的CFAR目标检测。

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