阵列误差影响下的RBF神经网络波达方向估计

针对阵列误差(阵元间互耦、通道失配)影响下波达方向估计问题,提出一种新型的基于径向基神经网络侦察测向系统。这种系统采用直接数据域补偿算法对输入数据进行误差补偿,从而获得正确的基函数中心。在无需对RBF神经网络测向系统作任何改进的情况下,可获得对波达方向的准确估计。为了减少输入,利用信号协方差矩阵的对称性以及对角线元素不包含信号方向信息的特点,仅考虑协方差矩阵中的上三角部分元素作为网络输入。给出了应用该方法的具体步骤。仿真实验表明,基于这种RBF网络的侦察测向系统达到了很高的精度。

Direction of Arrival (DOA) Estimation for an Array with Errors Using RBF Neural Network

A novel direction finding system based on radial-basis function neural network is proposed to solve the problem of direction of arrival estimation for an array with system errors(mutual coupling and mismatching).Through calibration of input data with direct data domain algorithm,the correct centers of radial-basis function can be obtained.Direction of arrival can be estimated without improving the radial-basis function neural network DOA estimation system.In order to reduce the dimension of input vectors,the symmetry property in the correlation matrix is utilized.Only the upper triangular half of the correlation matrix is used in processing.The specific steps are presented.The simulation results demonstrated that this DOA estimation system has very high precision.