根据协方差矩阵的性质，构造了波达方向矩阵。
A matrix, called the Direction of Arrival (DOA) matrix, is formed from the covariance matrices.
利用空间四阶累量的孔径扩展性质，构造了一种新的累量域虚拟阵列波达方向矩阵。
A new type cumulant-based virtual DOA matrix is formed using the property of aperture extension of fourth-order cumulants.
本文利用两个具有位移特性的二维传感器子阵列信息构成一种新的矩阵——混合波达方向矩阵。
A new type matrix-mixed DOA matrix is formed with the information of two identical translation subarrays.
利用虚拟累量域波达方向矩阵的特征值的幅值和相位信息，就可以求出信号源的方位角和俯仰角。
The azimuth and elevation of the incident sources can be estimated respectively from the amplitude and phase information of the eigenvalues of the new matrix.
对四阶累量混合波达方向矩阵进行特征分解，可实现有色高斯噪声背景中空域信号二维空间谱估计。
We can estimate two dimensional spatial spectra of sources in colour Guassian noises by eigen decomposing the matrix.
通过对相关矩阵进行特征值分解，估计信号子空间和噪声子空间，并利用MU S IC算法估计宽带LF M信号的波达方向。
Through estimating the signal and noise subspaces with the eigen-decomposition of the correlation matrix, the MUSIC algorithm is used to estimate the DOAs of LFM sources.
通过构建空间时频分布矩阵，和传统的阵列信号处理方法相结合，从而得到一种新的时频域的波达方向估计方法。
It presents a new method of DOA estimation in time-frequency domain, via establishing the STFD matrix and combining the traditional methods of array.
基于互耦矩阵的特殊结构，给出了一种更具一般性的非均匀圆阵模型，提出了一种在未知互耦条件下的非均匀圆阵波达方向估计算法。
Based on the special structure of coupling matrix, a direction of arrival (DOA) estimation algorithm in the presence of unknown mutual coupling for the nonuniform circular array (NUCA) is presented.
根据系统数据矩阵不存在扰动和存在扰动两种情况，分别给出波达方向的最小二乘估计和总体最小二乘估计。
Under the circumstances of no perturbation and with perturbation in coefficient matrix, both LS and TLS estimators were proposed.
根据系统数据矩阵不存在扰动和存在扰动两种情况，分别给出波达方向的最小二乘估计和总体最小二乘估计。
Under the circumstances of no perturbation and with perturbation in coefficient matrix, both LS and TLS estimators were proposed.
应用推荐