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Ocean duct inversion from radar clutter using Bayesian-Markov chain Monte Carlo method

Sheng Zheng Huang Si-Xun Zeng Guo-Dong

Ocean duct inversion from radar clutter using Bayesian-Markov chain Monte Carlo method

Sheng Zheng, Huang Si-Xun, Zeng Guo-Dong
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  • Abstract views:  3950
  • PDF Downloads:  1243
  • Cited By: 0
Publishing process
  • Received Date:  22 July 2008
  • Accepted Date:  04 August 2008
  • Published Online:  05 March 2009

Ocean duct inversion from radar clutter using Bayesian-Markov chain Monte Carlo method

  • 1. 解放军理工大学气象学院,南京 211101

Abstract: Using the Bayesian-Markov chain Monte Carlo (MCMC) method, based on the measurement information of radar clutter(electromagnetic propagation loss),we obtain the posterior probability density of the duct parameter by describing the prior information of the duct parameter as the prior probability density. And then, Gibbs sampler of the MCMC method is used to sample the posterior probability density. The sample maximal likelihood is regarded as an evaluation of the duct parameter distribution. The results of simulation experiment show that this set of methods make good use of the prior information and the inversion precise is better than the genetic algorithm. In addition, it is capable of describing (definite or indefinite) prior information in a convenient and controllable way, as well as capable of giving the complete solutions, which is very important to practical applications.

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