一种强噪声环境下的水声信号提取算法研究

摘要：

在对水中目标进行探潜、 跟踪、 定位时， 需要对目标辐射的水声信号进行频域分析、 相关性计算等处理。 在强噪声环境下， 目标的信号可能会被噪声淹没， 导致无法有效识别目标。 针对这一问题， 本文提出利用傅里叶降噪预处理与小波变换相结合进行信噪分离， 实现强噪声环境下的水声信号提取。 设计了傅里叶系数阈值调整与小波阈值变换相结合的组合算法， 并对算法的性能进行了测试。 仿真实验表明， 在信噪比为-15 dB时， 该组合算法能够实现水声信号的有效提取， 并将信噪比提高到了8.2 dB。

In the exploration, tracking and positioning of underwater targets, it is necessary to perform frequency domain analysis and correlation calculation on the underwater acoustic signals of the target radiation. In a strong noise environment, the target signal may be overwhelmed by noise, resulting in an inability to effectively identify the target. Aiming at this problem, this paper presents a method of signal-noise separation by combining Fourier denoising with wavelet transform to realize underwater acoustic signal extraction in a strong noise environment. The combination algorithm of Fourier coefficient threshold adjustment and wavelet threshold transform is designed, and performance of the algorithm is tested. Simulation results show that the combination algorithm can effectively extract underwater acoustic signals when signal-to-noise ratio (SNR) is -15 dB, which can improve the SNR to 8.2 dB.