色噪声背景下基于特征空间的信源估计新方法

摘要

准确估计信源数目是很多高分辨算法得以实现的前提条件.传统的信源估计方法大多是在白噪声背景下,以数据协方差矩阵的特征值序列作为研究对象,按照某种标准设定门限来进行判决估计信源数目.而在实际情况中白噪声很难满足,从降一维特征空间的投影矩阵角度出发,获得数据协方差矩阵的局部数据的投影差值序列,从而有效避开了噪声主要能量的影响,对空间色噪声也有一定的抑制效果.仿真结果表明在色噪声背景下,利用该方法可以在多信源情况下准确估计信源数目.%To detect the number of signals correctly is the prerequisite for many algorithms with high resolution. The conventional approaches usually focus on eigenvalue of covariance matrix to set the threshold according to some criterion, in order to estimate the number of signals in a white noise background. However, there exists no white noise actually. This paper starts from the perspective of one-dimension-reduced projection matrix of eigenspace and obtains the difference sequence of projection of the part covariance matrix, which effectively avoids the impact of the principal noise energy, thus restrains the colored noise in some sense. The simulation results illustrate the new method can estimate the correct number of multi-signals in the background of colored noise.