一种迭代可分离的机载面阵雷达杂波抑制方法

为了解决传统空时自适应处理方法由于独立同分布训练样本不足无法有效抑制机载面阵雷达非均匀杂波的问题,提出了一种迭代可分离的机载面阵雷达杂波抑制方法。该方法首先通过雷达系统和载机平台运动参数先验知识构造杂波表示基矩阵,然后基于协方差矩阵匹配估计准则分别估计待检测单元的杂波空域和时域功率谱,接着按照线性约束最小方差准则计算待检测单元的空域和时域部分权向量,最后再结合杂波参数化模型和得到的空域和时域部分权向量计算空时滤波权向量用于处理待检测单元回波数据。该方法不需要训练样本,不需人为设置超参数,具有全局收敛性,即使存在距离模糊也可以有效地抑制机载面阵雷达回波数据中的非均匀杂波。仿真实验说明了本文方法的有效性。

Iteration-separable clutter suppression method for airborne planar array radar

To solve the problem that the traditional space-time adaptive and processing method cannot effectively suppress the heterogeneous clutter due to lack of enough independent identically distributed training samples, an iteration-separable clutter suppression algorithm for airborne planar array radar is proposed. Firstly, the clutter representation basis matrix is constructed based on some priori information such as radar system and aircraft platform motion parameters. Then, the spatial and temporal clutter power spectrum of cell under test (CUT) are separately estimated by the covariance matching estimation criterion. Next, the spatial and temporal partial weights are calculated through the linearly constrained minimum variance criterion. Finally, combined with the clutter parameterized model and the obtained spatial and temporal partial weight vectors, the space-time filtering weight vector is calculated to process the CUT echo data. The proposed method is hyperparameter-free, which is global convergent and does not need the training samples. In addition, the proposed method can effectively suppress the heterogeneous clutter of echo data of airborne planar array radar even if range ambiguity exists. Simulation results demonstrate the effectiveness of the proposed method.