基于特征子空间投影的信源数估计方法

为了适应实际测向系统的环境，针对常规信源数估计方法在色噪声背景下估计性能变差的问题，提出了基于特征子空间投影的信源数估计方法。首先对特征向量分组，获得只含有噪声部分和既含有噪声又含有信号部分的特征子空间。阵列的导向矢量阵与噪声子空间正交，而与信号子空间张成的是同一个空间。根据这个原理，将协方差矩阵在不同特征子空间上进行投影，得到存在差异的投影数据。最后对投影数据进行求方差处理，得到投影方差，将其作为信源数估计的依据，进而实现信源数估计。仿真实验和实测数据测试表明了该算法的正确性和有效性。

Estimation of the number of signals based on characteristic subspace projection

In order to adapt to the actual direction finding system, aiming at the problem that the estimation of performance reveals a change for the worse when using the conventional method of estimating the number of signals in colored noise field, a new approach based on characteristic subspaces projection is proposed. First, grouping the eigenvectors, the eigen-subspaces which only contain noise subspace and the other contain both noise and signal subspace are received. The array manifold matrix is orthogonal to the noise subspaces of the covariance matrix, and it has the same expanded space with the signal subspaces. According to this principle, the covariance matrix is projected on the eigen-subspaces, so projection data are received. Finally, the variance of the projection data is calculated, then the projection variance is received and is regarded as the evidence for signals number estimation, and the number of signals is estimated. Computer simulation and measured data test show the correctness and effectiveness of the algorithm.