一种改进的基于低秩逼近的空时自适应处理算法

发布时间：2019-01-27 23:14

【摘要】：针对非均匀杂波情况下的空时自适应处理的小样本问题,该文提出一种基于权矩阵低秩逼近的空时自适应处理方法。与传统的低秩逼近算法不同,利用空时导向矢量特殊的克罗累计性,该文重新构造新的权矩阵,使得该权矩阵的行数与列数尽可能地相近或相同,以减少算法所需的样本个数和计算量。采用低秩逼近方法对新构造的权矩阵进行表示,则原二次优化问题转化为求解一个双二次代价函数问题。实验表明,改进的空时权矩阵低秩逼近方法能有效地提高空时自适应处理的收敛速度和降低算法复杂度。
[Abstract]:For the small sample problem of space-time adaptive processing in the case of non-uniform clutter, this paper presents an adaptive space-time processing method based on low-rank approximation of weight matrix. Different from the traditional low rank approximation algorithm, this paper reconstructs a new weight matrix by using the special Kroth cumulativeness of space-time guidance vector, so that the number of rows of the weight matrix is as close or the same as the number of columns as far as possible. To reduce the number of samples needed and the amount of computation needed by the algorithm. If the new weight matrix is represented by the low rank approximation method, the original quadratic optimization problem is transformed into a biquadratic cost function problem. Experiments show that the improved space-time weight matrix low rank approximation method can effectively improve the convergence speed and reduce the complexity of space-time adaptive processing.
【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;西北大学信息科学与技术学院;
【基金】：国家自然科学基金(61271293) 陕西省自然科学基金(2013JM8008)资助课题
【分类号】：TN959.73

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