非正侧阵机载雷达杂波谱迭代自适应配准方法

发布时间：2018-12-30 13:23

【摘要】：对于机载非正侧阵雷达,杂波谱的距离空变性使得直接利用邻近单元数据估计的协方差矩阵与真实协方差矩阵不匹配,导致空时自适应杂波抑制性能下降。基于配准的补偿(registration-based compensation,RBC)方法通过时域平滑来估计空时谱,继而对地杂波的距离依赖性进行补偿,由于时域孔径损失使杂波谱峰值的估计精度受到限制。针对这一问题,考虑到杂波空时谱的稀疏性,本文利用迭代自适应算法(iterative adaptive approach,IAA)进行空时谱估计,并重构各辅助距离单元协方差矩阵以实现杂波谱配准,称为IAA-RBC算法。由于该算法不存在孔径损失,杂波谱配准精度更高。仿真实验表明,即使在样本中存在目标污染等干扰因素的情况下,所提方法相比传统的利用时域平滑的RBC方法也能获得更好的信噪比改善。
[Abstract]:For airborne non-positive and side-array radars, the range space variability of clutter spectrum makes the covariance matrix estimated directly using adjacent cell data mismatch with the real covariance matrix, which leads to the degradation of space-time adaptive clutter suppression performance. Based on registration compensation (registration-based compensation,RBC) method, space-time spectrum is estimated by time-domain smoothing, and then the distance dependence of ground clutter is compensated. Due to the loss of aperture in time domain, the estimation accuracy of the peak value of clutter spectrum is limited. To solve this problem, considering the sparsity of clutter space-time spectrum, an iterative adaptive algorithm (iterative adaptive approach,IAA) is used to estimate space-time spectrum, and the covariance matrix of each auxiliary distance unit is reconstructed to achieve clutter spectrum registration. Called IAA-RBC algorithm. Because the algorithm has no aperture loss, the precision of clutter spectrum registration is higher. Simulation results show that the proposed method can improve SNR better than the traditional time-domain smoothing RBC method even in the presence of interference factors such as target pollution in the sample.
【作者单位】：西安电子科技大学雷达信号处理国家重点实验室;
【基金】：国家自然科学基金(61372133)资助课题
【分类号】：TN957.51

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