基于谐波恢复的状态空间模型的互高阶累计量Ls-Hankel矩阵分解法

Ls-Hankel matrix decomposition of cross-high-order cumulant based on state space model of harmonic retrieval

将状态空间模型与互高阶累计量结合在一起,首次提出基于谐波恢复状态空间模型的互高阶累计量的Ls-Hankel矩阵分解法。仿真结果表明,该方法在混合色噪声和很低信噪比条件下谱估计的分辨率、稳定性及对混合色噪声的抑制等方面均明显优于自高阶谱估计方法。

Combining the state space model with cross-high-order cumulant, a new method for harmonic retrieval through least-square-Hankel matrix decomposition under colored noises background was proposed. The simulation results showed that the proposed spectrum estimation method is better than the Esprit method of auto-high-order cumulant in the identification rate and the stability under the conditions of colored noise background and low signal-to-noise ratio as well as in the ability to overcome the colored noise disturbance.