基于酉变换-矩阵束的稀布线阵方向图综合
发布时间：2019-03-19 18:14
【摘要】：该文提出一种非迭代的稀布线阵方向图综合方法。该方法首先对方向图采样数据进行centro-Hermit化处理,然后通过酉变换构造等价实矩阵束,得到非均匀单元位置与新矩阵束广义特征值的关系。在此基础上,对实矩阵奇异值分解,并舍弃非主要奇异值以获得低阶左奇异向量矩阵,进而求得稀布阵列的阵元位置和相应激励。相比于其他方法,该方法能够直接得到阵元位置的实数解,奇异值分解和特征值分解均在实数域进行,提高逼近程度的同时有效降低了计算量,仿真验证了该方法利用少量阵元即可高效实现线阵的方向图综合。
[Abstract]:In this paper, a non-iterative method for pattern synthesis of rarefied linear arrays is proposed. In this method, the data sampled from the square graph is processed by centro- Hermitization, then the equivalent real matrix bundle is constructed by unitary transformation, and the relation between the position of the non-uniform element and the generalized eigenvalues of the new matrix bundle is obtained. On this basis, the singular value decomposition of the real matrix and the abandonment of the non-main singular value to obtain the low-order left singular vector matrix, and then the position of the element and the corresponding excitation of the rarefied array are obtained. Compared with other methods, this method can get the real solution of element position directly. Singular value decomposition (SVD) and eigenvalue decomposition (EVD) are carried out in the real number domain, which improves the degree of approximation and effectively reduces the computational complexity. Simulation results show that the proposed method can efficiently realize the pattern synthesis of linear arrays by using a small number of array elements.
【作者单位】： 空军工程大学信息与导航学院;
【基金】：国家自然科学基金(61172148)~~
【分类号】：TN820.12
本文编号：2443769
[Abstract]:In this paper, a non-iterative method for pattern synthesis of rarefied linear arrays is proposed. In this method, the data sampled from the square graph is processed by centro- Hermitization, then the equivalent real matrix bundle is constructed by unitary transformation, and the relation between the position of the non-uniform element and the generalized eigenvalues of the new matrix bundle is obtained. On this basis, the singular value decomposition of the real matrix and the abandonment of the non-main singular value to obtain the low-order left singular vector matrix, and then the position of the element and the corresponding excitation of the rarefied array are obtained. Compared with other methods, this method can get the real solution of element position directly. Singular value decomposition (SVD) and eigenvalue decomposition (EVD) are carried out in the real number domain, which improves the degree of approximation and effectively reduces the computational complexity. Simulation results show that the proposed method can efficiently realize the pattern synthesis of linear arrays by using a small number of array elements.
【作者单位】： 空军工程大学信息与导航学院;
【基金】：国家自然科学基金(61172148)~~
【分类号】：TN820.12
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