海杂波背景下基于FRFT的多运动目标检测快速算法

A Fast Detection Algorithm of Multiple Moving Targets in Sea Clutter Based on FRFT

  • 摘要: 针对海杂波背景中多运动目标检测问题,建立了目标检测和参数估计模型,结合小波包变换(WPT)的多尺度分辨能力和分数阶Fourier变换(FRFT)对线性调频(LFM)信号良好的能量聚集性的特点,提出了一种应用小波包变换的FRFT域动目标检测算法。算法采用“最小Shannon熵”标准确定最优小波树,利用阈值删除技术,对不同频段信号进行滤波,达到抑制海杂波的目的;经分数阶Fourier变换后,取峰值的绝对值作为检测统计量,与门限进行比较后判断目标的有无。采用分级迭代运算的方法估计目标参数,大大提高了运算速度,降低了运算量;借鉴“CLEAN”思想,有效地解决了强目标对弱目标的遮蔽影响。经X波段实测海杂波数据验证,算法具有良好的检测海杂波中微弱动目标的能力。

     

    Abstract:  On the basis of the detection and parameter estimation model of multiple moving targets, a new algorithm based on wavelet packet transform (WPT) and fractional Fourier transform (FRFT) is proposed for weak moving targets detection in sea clutter. The multi-resolution property of WPT and the characteristic of good energy concentration on LFM signal in FRFT domain are combined together. At first, optimal wavelet tree is calculated using “minimum Shannon entropy” and threshold censored method is used to suppress sea clutter of different frequency bands. Then, take the absolute amplitude of signal after FRFT as test statistic and search for peaks in two dimensions with the threshold. Grading iterative method is used for parameter estimation with fast calculation and the shading problem between multiple targets is solved through “CLEAN” method. In the end, IPIX real sea clutter data is used for verification and the results indicate that the proposed algorithm has a good performance of detecting multiple moving targets in low SCR conditions (about -10dB). It proves that the algorithm can improve operational speed and precision, and also be of better anticlutter interference capability.

     

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