基于 Bayes-MCMC 的水声双程信道建模及自适应采样反演

Gang Zhao, Nai Wei Sun, Shen Shen, Yi Xin Yang

科研成果: 期刊稿件文章同行评审

摘要

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.

投稿的翻译标题Parameter Adaptive Sampling Inversion of Underwater Acoustic Go-back Channel Model Based on Bayes-MCMC
源语言繁体中文
页(从-至)774-786
页数13
期刊Journal of Unmanned Undersea Systems
30
6
DOI
出版状态已出版 - 12月 2022

关键词

  • Bayes-MCMC
  • echo-signal inversion
  • underwater acoustic go-back channel
  • underwater operation equipment

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