子空间分解法在声目标特征提取中的应用

研究用于识别直升机目标声信号的特征提取方法，方法通过对直升机信号频特征分析，采用基于子空间分解的多重信号分类法算法提取信号谐波频率作为目标特征，利用子空产妥将观测数据分解为信号子这僮与噪声子空间特点，抑制噪声干扰，提高识别能力。

Application of Subspace Decomposition in Feature Extraction of Acoustic Targets

Aim To investigate the technique of feature extraction for helicopter identification. Methods Based on the analysis of spectral characteristics of a helicopter acoustic signal, a method of subspace decomposition was proposed for the purpose of suppressing noise interference and increasing the ability of recognizing target and multiple signal classification(MUSIC), an algorithm of harmonic retrieval, was introduced to extract harmonic frequencies from acoustic signals. Results and Conclusion By using MUSIC harmonic frequencies were extracted from really measured helicopter acoustic signals. The results show that it is feasible to extract features in frequency domain from acoustic signals with the method of subspace decomposition and MUSIC is an effective algorithm of extracting harmonic frequencies.