基于多层混合模型的非高斯海洋背景场表示

Representation of Non-Gaussian Ocean Background Field Based on Hierarchical Mixture Model

实际的海洋环境背景声场通常不服从高斯分布,此情况下多种水声信号处理方法的前提条件得不到满足。针对非高斯海洋背景场下的噪声预处理,研究了一种具有促稀疏性的多层贝叶斯建模方法,使用吉布斯采样对变量的后验概率进行求解。对两组在不同海域采集的水声数据进行建模,分析结果表明非高斯背景场中高阶分量混合系数虽然较小。

The real ocean background acoustic field is usually not subjected to the Gaussian distribution,which violates the precondition of many processing methods of underwater acoustic signal. For the problem of noise pretreatment in non-Gaussian background field,a hierarchical Bayesian model which promotes the sparsity is studied and conditional probabilities are derived using Gibbs sampling. Two different sets of underwater acoustic data are modeled using the proposed method and the results indicate that the high order components are important for the accurate description of the real distribution,although they have smaller mixture coefficients.