本文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 Based on the fourth-order cumulant, we prove for the first time that the high-order cumulants can effectively suppress the uncorrelated noise and the Gaussian noise. Based on the Yule Walker equation of mutual high-order cumulants, Value decomposition, the signal vector space and the noise vector space are established. The Pisarenko method of mutual high-order spectrum estimation of sinusoidal parameters in mixed noise background is proposed for the first time. The simulation results show that this method has better resolution and spectral estimation stability than the high-order Pisarenko method, and has better anti-interference ability and lower working threshold of signal-to-noise ratio. It is especially suitable for Engineering small and medium signal measurement