前视阵高速雷达空时处理方法研究

多普勒严重模糊,训练样本有限是高速平台雷达面临的重要问题,协方差矩阵估计误差以及目标约束误差将使处理器性能严重下降。针对上述问题,该文对前视阵杂波自由度进行了研究,分析表明杂波特征谱与孔径带宽积、时宽带宽积以及空时耦合特性有关。该文提出基于主瓣区域空时多波束的鲁棒空时处理方法,首先通过空时多波束降低杂波自由度,然后利用多普勒区间约束的方法,提高了处理器的性能和系统鲁棒性。仿真实验证明了该文方法的有效性,当样本中存在目标信号时,该文方法相比传统固定约束矢量的方法输出信杂噪比性能平均提高5 dB左右。

Research on STAP Approach of Forward Looking Array Radar with High-velocity

The seriously expended clutter Doppler and finite sample supports are the problem of high velocity radar platform, and the performance of conventional Space Time Adaptive Processing (STAP) will degrade due to covariance matrix error or inaccurate target constraint. A research on clutter Degree of Freedom (DoF) of forward-looking radar is discussed. The eigenvalue spectrum of clutter covariance matrix is relative with aperture bandwidth product, time-width bandwidth product together with the correlation of spatial and temporal frequency. Robust STAP method based on space-time multi-beam transforming is proposed. First, the DoF of clutter is reduced through space-time multi-beam transforming. Then, the extended Doppler constrain method is used to improve the performance and robustness of the processer. The numerical simulations show the effectiveness of the proposed method. Even when the training data contains the target signal, the proposed robust method can maintain up to 5 dB Signal-to-Clutter-plus-Noise Ratio (SCNR) improvement compared with the conventional methods.