Parameter Adaptive Sampling Inversion of Underwater Acoustic Go-back Channel Model Based on Bayes-MCMC

High-confidence underwater acoustic go-back channel modeling is an essential part of the study of target echo simulation and plays an important role in the development of underwater operation equipment. Based on the classical channel model and reasonable assumptions, an analytical model of an underwater acoustic go-back channel is established. Using the Bayes-MCMC inversion algorithm as the core, the characteristics of the inversion problem of underwater acoustic channel parameters were analyzed, and the Metropolis-Hastings adaptive single-dimension serial sampling algorithm was designed to realize efficient channel model parameter inversion based on echo signals. The results of the simulation and measured data show that the proposed adaptive sampling inversion method has good consistency and convergence and has good engineering application prospects in underwater operation equipment simulation tests.