抗频移声谱特征提取及目标分类应用研究

针对目标运动等导致的辐射噪声频谱特征的时变性对目标分类稳定性的影响,提出一种基于时频图像累积变换的抗频移声谱特征提取方法,不仅能够提取淹没在强噪声中的线谱信号,还能够实时给出谱线的参数信息,同时结合听觉特征识别原理,采用抗频移的仿倍频程的三角滤波法提取目标特征。仿真和实际数据处理表明,所提出的特征有助于探测设备克服目标未知的复杂运动带来的频谱时变影响,提高了分类特征的稳定性。

Spectral shift invariant feature extraction and its application in underwater target classification

In view of the influence of time variability of the spectrum feature of radiated noise caused by the target motion on the stability of target classification, a spectral shift invariant feature extraction method based on the time frequency image accumulation transform is proposed. It can not only extract the line spectrum signal submerged in the strong noise, but also can give the parameter information of the spectrum line in real time, and meantime combine the parameters of the spectrum line. Based on the principle of auditory feature recognition, the target features are extracted by the anti-frequency-shift modeled octave trianglar filtering method. The simulation and actual data processing show that the proposed features help the detection device overcome the time-varying influence of the spectrum caused by the unknown complex motion of the target and improve the stability of the classification features.