基于经验模式分解的拖曳式声纳拖船噪声抵消研究

Tow ship noise cancellation using empirical mode decomposition

拖曳式线列阵声纳的拖船噪声具有多途角扩展等特点,并且是一个非平稳过程,使得对该噪声的消除或抑制是一大难点。经验模式分解是一种用于分析非线性非平稳信号的新方法,该方法自适应地将嵌于数据内部的多个固有模式函数逐一分解开来。本文尝试利用经验模式分解方法分离出水听器接收信号中的拖船干扰噪声,从而达到消除干扰的目的。海上试验数据的处理结果充分验证了这种方法的可行性。

Tow ship noise is a nonstationary process with several characteristic properties, such as multi-path and angle dispersion, which greatly add the difficulty to cancel or suppress the noise. Empirical Mode Decomposition （EMD） is a novel method used for processing nonlinear and nonstationary signals. Finite Intrinsic Mode Functions （IMFs） are derived from the data adaptively. EMD is used here as a signal separation tool to separate the tow ship noise from the received signal. Sea trial data are used to verify its feasibility, and the result is promising.