基于最大相关熵准则的水下生物脉冲噪声消除方法

近海生物噪声表现为脉冲噪声，这一类噪声显著降低了水声通信系统的性能。结合水声信道的稀疏特性，提出一种基于最大相关熵准则的级联滤波器算法，该算法实现了脉冲噪声的消除及稀疏信道估计。第一级自适应滤波器完成对噪声的消除工作，第二级滤波器对去噪后的信号进行稀疏信道估计。该方法的优势在于无需知道信号和噪声的相关信息。仿真结果表明，提出的方法比单一的滤波器结构和传统信道估计算法性能更加优越。

A method of eliminating underwater biological impulse noise based on maximum correntropy criterion

Offshore biological noise appears as impulse noise. This type of noise significantly reduces the performance of underwater acoustic communication systems. Combined with the sparse characteristics of underwater acoustic channels, a cascade filter algorithm based on maximum correntropy criterion is proposed to realize impulse noise elimination and sparse channel estimation. The first-stage adaptive filter completes noise elimination, and then the second-stage filter performs sparse channel estimation for the signals after denoising. The advantage of this method is no need to know the relevant information about signal and noise. Simulation results show that the proposed method is better than the single filter structure and the traditional channel estimation algorithm.