海杂波背景下基于FRFT的自适应动目标检测方法

An Adaptive Detection Algorithm for Moving Target at Sea in FRFT Domain An Adaptive Detection Algorithm for Moving Target at Sea in FRFT Domain

  • 摘要: 本文主要研究了海杂波背景下微弱动目标检测问题,将基于统计理论的LMS算法和基于分数阶Fourier变换的动目标检测方法相结合,引入到海杂波微弱动目标检测中,并在此基础上提出一种分数阶Fourier域自适应动目标检测算法。首先建立了时变幅度的动目标检测模型,采用峰度检测的方法,通过计算目标回波分数阶Fourier域幅值的峰度值,分级迭代运算,确定最佳变换角度,既保证了参数估计精度,又降低了计算量。然后,构造分数阶Fourier域自适应谱线增强器,抑制海杂波,提高信杂比;将泄漏因子引入到加权矢量的迭代公式中,降低记忆效应对谱线增强器的影响;并对自适应步长进行功率归一化,提高收敛速度;输出信号在分数阶Fourier域与门限进行比较后判断目标的有无,估计出目标的运动参数。最后,采用X波段IPIX雷达海杂波数据进行验证,结果表明算法具有较快的收敛速率和较小的均方误差,在低信杂比条件下(SCR=-5dB)具有较高的检测概率(Pd=0.9),证明了算法的有效性和稳健性。

     

    Abstract: In this paper, weak moving target detection in sea clutter is mainly studied. A novel adaptive fractional Fourier transform (FRFT) based algorithm is proposed for moving target detection in sea clutter, which combines LMS algorithm and FRFT method. At first, detection model of moving target with time-varying amplitude is established and the optimal transform angle is determined by calculating kurtosis of amplitude in FRFT domain. Grading iterative method is used for good accuracy of parameter estimation and fast calculation speed. Then, adaptive FRFT domain line enhancer (ALE) is employed to suppress sea clutter and improve signal to clutter ratio (SCR). Leakage factor is introduced into the update equation of weight vector to reduce memory effects on ALE and step size is normalized by the power of input signal with fast convergence. Target can be declared if the output signal is higher than the threshold and then parameters of moving target are estimated. In the end, X-band real sea clutter of IPIX radar is used for verification and the results present that the proposed algorithm has good convergence property and small mean square error (MSE). Weak moving target can be detected in low SCR (SCR=-5dB) environment with high detection probability (Pd=0.9), which indicates the effectiveness and robustness of the algorithm.

     

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