Bayes匹配场地声参数反演:多步退火Gibbs采样算法

摘要

A multi-annealing Gibbs (multi-AG) sampling algorithm is developed to obtain a fast,accurate inversion result of ocean geoacoustic parameters.The proposed algorithm can deal well with huge computation load and high side lobe in multi-dimensional inversion of Bayes matched-field,and also eliminate the effects from the sampling bounds.The sensitivity of geoacoustic parameters to the matchedfield processor is analyzed,which contributes to establish the multi-step inversion and annealing scheme.The Gibbs sampling algorithm is used to invert the highest sensitive parameters,which mean value is necessary to the following inversion steps.The inversion of remain parameters can be operated with annealing Gibbs sampling algorithm step by step.The inversion effects of Metropolis-Hastings,Gibbs,FGS,and multi-AG algorithms are compared through numerical experiment,and the research shows that multi-AG sampling algorithm can be used to obtain the inversion results with the smallest mean square deviation and the highest precision,while costing the least algorithm computation.%为实现海洋地声环境参数的快速高效反演,提出多步退火Gibbs (Multi-AG)采样算法,可消除因参数搜索空间设置对参数反演结果的影响,并有效解决Bayes匹配场高维参数反演过程中常见的运算量大、旁瓣高等问题.分析待反演地声参数对匹配场处理器的敏感性,用以制定多步反演与退火方案,利用Gibbs采样算法反演敏感性级别最高的参数,计算其均值并代入后续反演步骤,进而采用退火Gibbs采样算法逐步反演后续参数;利用数值仿真实验对比Metropolis-Hastings算法、Gibbs采样算法、快速Gibbs采样算法和Muhi-AG采样算法的反演效果.实验结果表明,与其他3种算法相比,Multi-AG采样算法可通过最小的计算量得到均方差最小、精度最高的参数反演结果.