基于正交小波分解的线谱增强算法研究

The study of a line spectrum enhancement method based on orthogonal wavelet transform

介绍了传统线谱增强器(ALE)结构,分析了ALE的工作原理。ALE线谱增强的原因是降低了基本输入和参考输入中的噪声相关性,由于对参考输入的权系数调整无法对噪声进行合理估计,正弦信号得到增强。正交小波分解能将信号分解为尺度子空间和小波子空间中的2部分,同时2子空间正交。利用正交小波分解的这一特性,将尺度子空间中的逼近部分作为自适应滤波器的参考输入,使得参考输入和原信号中的噪声相关系数很小。对高斯环境下正弦信号和某水中目标实测信号进行了算法仿真,研究了该线谱增强算法的性能。结果表明,该算法在对高斯噪声环境和非平稳、非高斯目标实测信号中的线谱增强效果均优于ALE。

The structure of traditional adaptive line spectrum enhancer（ALE）is introduced, and the principle of ALE is analyzed. Line spectrum enhancement is acquired by reducing the noise correlativity between basic input and reference input. The noise of origin signal can＇t be properly estimated by adaptively adjusting weight coefficient, so the sinusoids signal is enhanced. Using orthogonal wavelet decomposition, the signal can be decomposed into two parts--one belongs to the scale subspace and the other belongs to the wavelet subspace. The two subspaces are orthogonal. So the part belongs to scale subspace works as the input signal of the adaptive filter, accordingly the optimal filtering method of line spectrum enhancer is realized. The simulation line spectrum and certain underwater object radiated line spectrum are enhanced dynamically. The performance of the method is analyzed in detail. The results have shown that the new algorithm outperforms the ALE algorithm in handling non-stationary and non-gaussian noise and enhancing dynamic line spectrum, the proposed algorithms can be applied to improving the ability of underwater detection and weapon system.