基于小波包变换特征向量提取的隐蔽水声通信性能评价方法研究

Research on Performance Evaluation Method of Covert Underwater Acoustic Communication Based on Feature Vector Extraction with Wavelet Packet Transform

摘要:

针对水声通信系统的隐蔽性缺乏客观、有效的评价手段，提出一种基于小波包变换提取信号特征向量并比较特征向量相似度的信号隐蔽性评价算法。为了区别截获信号和环境噪声，考虑从能量分布特征的角度，提取截获信号的特征参数。所提算法利用小波包变换具有更高的时频分辨率、自适应选择频带等特点，获取信号的小波包能量占比、小波包能量熵、小波包尺度熵，采用上述 3 个特征参数组成特征向量和利用余弦相似度算法判别信号隐蔽性。仿真实验和海试结果表明，所提方法得到的信号隐蔽性能基本符合实际信号隐蔽性能随信噪比变化规律，为隐蔽水声通信系统评估设计和水声对抗性能评级提供有效参考。

关键词:隐蔽性能评估;隐蔽水声通信;小波包变换;特征提取;余弦相似度比较

Abstract:

To address the lack of objective and effective evaluation methods for the covert performance of underwater acoustic communication systems，an approach that relies on wavelet packet transform is proposed in this paper. The proposed method extracts signal feature vectors and utilizes a similarity algorithm to assess the covert capability of signals. The proposed method capitalizes on the superior time-frequency resolution and adaptive-frequency-band selection of the wavelet packet transform to differentiate intercepted signals from environmental noise. It extracts feature parameters of intercepted signals，specifically the wavelet packet energy percentage，wavelet packet energy entropy，and wavelet packet scale entropy. These parameters are used to construct the feature vectors，and the cosine similarity algorithm is applied to determine the covert performance of signals. Simulation experiments and sea trials demonstrate that the concealment performance yielded by the proposed method aligns closely with the actual changes in covert performance concerning signal-to-noise ratio. As a result，this method offers an effective reference for evaluating and designing covert underwater acoustic communication systems and grading the acoustic countermeasure performance.

Key words:covert performance evaluation;convert underwater acoustic communication;wavelet transform;feature extraction;cosine similarity algorithm