FRFT域内的海杂波多重分形特性与目标检测

发布时间：2018-04-28 06:24

本文选题：小目标 + 分数阶傅里叶变换　；参考：《南京大学学报(自然科学)》2017年04期

【摘要】：如何从海杂波中检测小目标是雷达信号处理研究中的一个热点问题.海杂波具有多重分形特性,利用海杂波和目标回波分形特性的不同进行区分:海杂波的复杂性决定了其分形维值一般较大,而海面目标由于表面规则平滑而分形维值较小.实际检测小目标时,海杂波较强,需要对其进行抑制,提高信杂比.分数阶傅里叶变换(Fractional fourier transform,FRFT)是一种提高信杂比(Signal to clutter ratio,SCR)的良好方法:动目标经过FRFT后,在最佳变换域可形成峰值,而海杂波难以积累出有效峰值.结合这些特性,本文提出了在FRFT域内多重分形特性联合检测小目标的方法.在多重分形基础上,比较了时域和FRFT域分形维轨迹,证明了FRFT能有效聚集目标单元能量,加大了纯海杂波与目标的差异.将FRFT域多重分形维和截距联合起来作为检测小目标的二维判决空间,用实测数据证明了海杂波和小目标在判决空间存在明显的差异性,验证了本文所提方法有效地提高了海杂波中小目标检测的能力.
[Abstract]:How to detect small targets from sea clutter is a hot issue in radar signal processing. Sea clutter has multifractal characteristics, which is distinguished by the difference between sea clutter and target echo fractal characteristics. The complexity of sea clutter determines that the fractal dimension of sea clutter is generally larger, while the fractal dimension of sea surface target is smaller because of the regular surface smoothness. When small targets are detected, the sea clutter is strong, so it is necessary to suppress it and improve the signal-to-clutter ratio. Fractional fourier transform (FRFT) is a good method to improve the signal-to-clutter ratio. After the moving target passes through the FRFT, the peak value can be formed in the optimal transform domain, but the sea clutter can hardly accumulate the effective peak value. Combined with these characteristics, this paper presents a method for joint detection of small targets by multifractal in FRFT domain. On the basis of multifractal, the fractal trajectories in time domain and FRFT domain are compared. It is proved that FRFT can effectively aggregate the energy of target unit and increase the difference between pure sea clutter and target. The multifractal and intercept in FRFT domain are combined as two dimensional decision space to detect small target. The difference between sea clutter and small target in decision space is proved by the measured data. It is verified that the proposed method can effectively improve the ability of small and medium target detection in sea clutter.
【作者单位】：南京大学电子科学与工程学院;
【基金】：江苏省基础研究计划(BK20151391)
【分类号】：TN957.51

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