非高斯相关杂波背景下雷达目标检测方法研究

Radar target detection method in non-Gaussian correlated clutter backgrounds

  • 摘要: 在非高斯相关杂波背景下,基于MTD(Moving Target Detection)的雷达目标检测性能严重下降。针对该问题,根据Alpha稳定分布杂波模型、分数低阶统计量理论,以输出信杂比最大为准则,提出了一种适用于非高斯相关杂波背景的雷达目标检测方法。该方法通过分解信号分数低阶协方差矩阵,计算等效杂波分数低阶协方差矩阵特征向量,得到最佳滤波器系数。通过仿真和实测数据,对所提出方法的检测性能进行了验证,并且与基于MTD的检测方法进行了比较,结果表明,在非高斯相关杂波背景下,所提方法的检测性能明显优于传统的MTD。

     

    Abstract: The radar target detection performance of the MTD(Moving Target Detection) method descend badly in non-Gaussian correlated clutter backgrounds. Therefore, a radar target detection method in non-Gaussian correlated clutter backgrounds is proposed. The proposed method is obtained by the rule of maximizing the output signal-to-clutter power ratio based on alpha stable clutter distribution model and the fractional lower order statistics. The proposed method obtained the optimum filter coefficient by decomposing the signal fractional lower order covariance matrix and computing the eigenvector of the clutter fractional lower order covariance matrix. Simulations and real data results show that, the detection performance of the proposed method obviously outperforms the traditional MTD method in non-Gaussian correlated clutter environments.

     

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