混合噪声背景下正弦参数估计的互高阶谱Pisarenko方法

本以互四阶累积量为依据，首次证明了互高阶累积量可以有效地抑制非相关噪声和高斯噪声；并在建立互高阶累积量的Yule-Walker方程的基础上，通过该矩阵的奇异值分解，建立了信号矢量空间与噪声矢量空间；首次提出了混合噪声背景下正弦参数估计的互高阶谱Pisarenko方法。仿真结果表明，与自高阶谱Pisarenko方法相比，该方法具有更好的谱估计的分辨率和谱估计的稳定性，抗干扰性更强，其信噪比工作门限更低，特别适合于工程中小信号的测量。

An Approach Based on Cross-High-Order Spectrum Pisarenko Method to Retrieve Sinusoidal Signal Buried in Hybrid Colored Noises

The cross high order cumulant (CHOC) such as the cross fourth order cumulant (CFOC) is firstly proposed to measure the signal and for the first time prove that the CHOC (CFOC) can control the non relevant noises and Gaussian noises. And based on the cross high order spectral (CHOS) Yule Walker equations, the sinusoidal signal matrix is decomposed by the way of singular value decomposition method. In the meantime the signal and noise vector spaces are presented and the method of Pisarenko is proved that it can efficiently distinguish the signal buried in the colored noises and has good robustness, so that this method is very suitable to be applied in projection.