RAPID CONVERGENCE RATE IN ADAPTIVE ARRAYS
RAPID CONVERGENCE RATE IN ADAPTIVE ARRAYS
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DOI：
10.1109/taes.1974.307893
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发表时间：
1974-01-01
影响因子：
4.4
通讯作者：
BRENNAN, LE
中科院分区：
文献类型：
--
作者：
REED, IS;MALLETT, JD;BRENNAN, LE
在许多应用中，自适应阵列的实用性受到其收敛速度的限制。这些系统中的自适应控制权重必须以等于或大于外部噪声场变化率的速率变化（例如，如果不使用步进扫描，则由于雷达中的扫描）。在具有大量自适应度的自适应系统以及噪声协方差矩阵的特征值相差很大的情况下，这种收敛速度问题最为严重。一种基于噪声场的样本协方差矩阵的自适应权重计算的直接方法已被发现在所有情况下提供非常快速的收敛，即独立于特征值分布。在Goodman早期工作的基础上，已经建立了一个理论，该理论预测了该技术可实现的收敛速率，并通过仿真得到了验证。
In many applications, the practical usefulness of adaptive arrays is limited by their convergence rate. The adaptively controlled weights in these systems must change at a rate equal to or greater than the rate of change of the external noise field (e.g., due to scanning in a radar if step scan is not used). This convergence rate problem is most severe in adaptive systems with a large number of degrees of adaptivity and in situations where the eigenvalues of the noise covariance matrix are widely different. A direct method of adaptive weight computation, based on a sample covariance matrix of the noise field, has been found to provide very rapid convergence in all cases, i.e., independent of the eigenvalue distribution. A theory has been developed, based on earlier work by Goodman, which predicts the achievable convergence rate with this technique, and has been verified by simulation.