Gibbs sampling for time-delay-and amplitude estimation in underwater acoustics

A stochastic volatility model incorporating the exponential power distributions is adopted in the present study to analyze exponentially decaying pulses in the presence of background noises of various magnitudes. The discussions are focused on its effectiveness in the determination of the instant of the pulse initiation and the decay constant. The results are compared with those obtained by the conventional short-time Fourier transform. It is found that the present stochastic volatility model can retrieve the instant of the pulse initiation and the decay constant within engineering tolerance even when the noise is slightly stronger that the pulse amplitude. Its performance is substantially better than that of the Fourier transform when the frequency of the decay pulse fluctuates.

Section: Gibbs Sampler For Ep-n Sv Modelsmentioning

confidence: 99%

On analysis of exponentially decaying pulse signals using stochastic volatility model

Chan

Tang

Wong

2006

“…Therefore, localization of one of the PPDF global extremes in the parameter space will lead to an effective estimation of relevant decay parameters, 6 the MAP estimation. Previous works have applied Gibbs sampling technique 6,14 within the Bayesian framework. Gibbs sampler breaks the problem of drawing samples from a multivariante density down to densities of smaller dimensionality in a rotational pattern.…”

Section: A Fast Search Algorithmmentioning

confidence: 99%

Evaluation of decay times in coupled spaces: An efficient search algorithm within the Bayesian framework

Xiang

Jasa

2006

This paper discusses an efficient method for evaluating multiple decay times within the Bayesian framework. Previous works [N. Xiang and P. M. Goggans, J. Acoust. Soc. Am. 110, 1415-1424 (2001); 113, 2685-2697 (2003); N. Xiang, P. M. Goggans, T. Jasa, and M. Kleiner, 117, 3707-3715 (2005)] have applied the Bayesian inference to cope with demanding tasks in estimating multiple decay times from Schroeder decay functions measured or calculated in acoustically coupled spaces. Since then a number of recent works call for efficient estimation methods within the Bayesian framework. An efficient analysis is of practical significance for better understanding and modeling the sound energy decay process in acoustically coupled spaces or even in single spaces for reverberation time estimation. This paper will first formulate the Bayesian posterior probability distribution function (PPDF) in a matrix form to reduce the dimensionality as applied to the decay time evaluation. Based on existence of only global extremes of PPDFs as observed from extensive experimental data, this paper describes a dedicated search algorithm for an efficient estimation of decay times.

“…͑14͒ is evaluated on a grid for r i and z si similar to the implementation in Ref. 20 and following the griddy Gibbs modeling of Ref. 21, because no closed form is known.…”

Section: ͑11͒mentioning

confidence: 99%

Multiple source localization using a maximum a posteriori Gibbs sampling approach

Michalopoulou

2006

Self Cite

Multiple source localization in underwater environments is approached within a matched-field processing framework. A maximum a posteriori estimation method is proposed that estimates source location and spectral characteristics of multiple sources via Gibbs sampling. The method facilitates localization of weak sources which are typically masked by the presence of strong interferers. A performance evaluation study based on Monte Carlo simulations shows that the proposed maximum a posteriori estimation approach is superior to simple coherent matched-field interference cancellation. The proposed method is also tested on the estimation of the number of sources present, providing probability distributions in addition to point estimates for the number of sources.