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中文摘要：
提出一种机载多输入多输出（MIMO）雷达降维空时自适应杂波抑制算法。首先将高维空时权向量重构为空域和时域权向量Kronecker积的形式,利用相关域信息,将最优空时处理的二次代价函数转化为两个二次代价函数,然后迭代求解两个二次代价函数中的两个低维权向量,分析表明该算法能有效降低计算量和估计采样协方差所需的训练样本数。最后,分别基于仿真和实测数据验证了算法的有效性。
英文摘要：
A reduced-dimension space-time adaptive processing（STAP） method for clutter suppression in airborne multiple-input multiple-output（MIMO） radar systems is developed.Firstly,the high-dimensional weight vector is decomposed into the Kronecker product of spatial and temporal weight vectors.Secondly,the quadratic cost function used in the optimum STAP is converted into two quadratic functions by using the information of the space-time correlation matrix.Finally,by iteratively optimizing two lower dimensional weight vectors in two quadratic functions,the proposed method can significantly decrease the computational load and training samples requirement.Experimental results using both simulated data and measured radar data demonstrate the effectiveness of the proposed method.
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