一种机载雷达两级降维空时二维自适应处理方法

 提出了一种机载相控阵雷达杂波抑制的两级降维空时自适应处理(STAP)方法，即：先根据杂波分布先验信息进行空时局域化(JDL)降维处理，然后对局域化输出进行多级维纳滤波(MWF)，实现二次降维。该方法综合了固定结构和自适应结构降维技术的优点，将JDL处理引入到MWF中，从而有效降低MWF的杂波自由度。计算机仿真和理论分析表明本文方法比JDL自适应处理方法和全空时MWF方法具有更小的运算量，对阵元随机幅相误差具有很好的容差能力，是一种稳健的两级降维自适应处理方法。最后，基于仿真和实测数据的实验验证了算法的有效性。

A Two-stage Dimension-reduced STAP Method for Airborne Radar

A two-stage dimension-reduced spatial-temporal adaptive processing (STAP) for clutter suppression and moving target detection in airborne radar system is proposed. Firstly, the spatial-temporal joint domain localization (JDL) is performed on the received signal by exploiting a-priori information about the location of clutter ridge in angle-Doppler space, and then the localized data are processed by the multistage wiener filter (MWF) method. The proposed method is the combination of fixed and adaptive dimension-reduced structures and has the advantage of less computing as complexity as compared with the JDL adaptive processing method and MWF method. Theoretical analysis and computer simulation results illustrate that the method can achieve robust performance without large loss in the presence of large random amplitude and phase errors existing in the array elements. Experiments results by using the measured data show the validity of the proposed method.