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

Multipath arrivals at a receiving sensor are frequently encountered in many signal-processing areas, including sonar, radar, and communication problems. In underwater acoustics, numerous approaches to source localization, geoacoustic inversion, and tomography rely on accurate multipath arrival extraction. A novel method for estimation of time delays and amplitudes of arrivals with maximum a posteriori (MAP) estimation is presented here. MAP estimation is optimal if appropriate statistical models are selected for the data; implementation, requiring maximization of a multidimensional function, is computationally demanding. Gibbs sampling is proposed as an efficient means for estimating necessary posterior probability distributions, bypassing analytical calculations. The Gibbs sampler includes as unknowns time delays, amplitudes, noise variance, and number of arrivals. Through Monte Carlo simulations, the method is shown to have a performance very close to that of analytical MAP estimation. The method is also shown to be superior to expectation-maximization, which is often applied to time-delay estimation. The Gibbs sampling approach is demonstrated to be more informative than other time-delay estimation methods, providing complete posterior distributions compared to just point estimates; the distributions capture the uncertainty in the problem, presenting likely values of the unknowns that are different from simple point estimates.     

Rapid-phase modulation of terahertz radiation for high-speed terahertz imaging and spectroscopy

Rapid voltage-controlled phase modulation of cw terahertz (THz) radiation is demonstrated. By transmitting an infrared beam through a lithium niobate phase modulator the phase of the THz radiation, which is generated by the photomixing of two infrared beams, can be directly modulated through a 2pi phase shift. The 100 kHz modulation rate that is demonstrated with this technique is approximately 3 orders of magnitude faster than what can be achieved by mechanical scanning.     

A particle filtering approach for spatial arrival time tracking in ocean acoustics

The focus of this work is on arrival time and amplitude estimation from acoustic signals recorded at spatially separated hydrophones in the ocean. A particle filtering approach is developed that treats arrival times as "targets" and tracks their "location" across receivers, also modeling arrival time gradient. The method is evaluated via Monte Carlo simulations and is compared to a maximum likelihood estimator, which does not relate arrivals at neighboring receivers. The comparison demonstrates a significant advantage in using the particle filter. It is also shown that posterior probability density functions of times and amplitudes become readily available with particle filtering.     

Measurement of the $$^{232}$$ Th(n,f) cross section with quasi-monoenergetic neutron beams in the energy range 2–18 MeV

The European Physical Journal A - The E1 contribution to the capture reaction $$^7\mathrm {Li}(n,\gamma )^8\mathrm {Li}$$  is calculated at low energies. We employ a coupled-channel...     

Particle filtering for passive fathometer tracking

Seabed interface depths and fathometer amplitudes are tracked for an unknown and changing number of sub-bottom reflectors. This is achieved by incorporating conventional and adaptive fathometer processors into sequential Monte Carlo methods for a moving vertical line array. Sediment layering information and time-varying fathometer response amplitudes are tracked by using a multiple model particle filter with an uncertain number of reflectors. Results are compared to a classical particle filter where the number of reflectors is considered to be known. Reflector tracking is demonstrated for both conventional and adaptive processing applied to the drifting array data from the Boundary 2003 experiment. The layering information is successfully tracked by the multiple model particle filter even for noisy fathometer outputs.     

Tabu for matched-field source localization and geoacoustic inversion

Tabu is a global optimization technique that has been very successful in operations research. In this paper, a Tabu-based method is developed for source localization and geoacoustic inversion with underwater sound data; the method relies on memory to guide the multiparameter search. Tabu is evaluated through a comparison to simulating annealing. Both methods are tested by inverting synthetic data for various numbers of unknown parameters. Tabu is found to be superior to the simulated annealing variant implemented here in terms both of accuracy and efficiency. Inversion results from the SWellEX-96 data set are also presented.     

ARTIFICIAL NEURAL NETWORK ANALYSIS IN INTERFEROMETRIC THz IMAGING FOR DETECTION OF LETHAL AGENTS

In the context of a non-invasive, non-contact method to detect concealed lethal agents employing stand-off imaging in the Terahertz (THz) range using an interferometric detector array, the techniques of image analysis are discussed. To complement the experimental testing, extensive modeling simulates reconstructed images of lethal agents at different THz frequencies applying interferometric techniques. The composite images are consequently analyzed using artificial neural network to make positive identification of the lethal agent. This work also attempts to address issues related to the presence of barriers and isolate some suitable numerical techniques required for rapid and successful recognition of lethal agents during security screening in THz range.     

Particle filtering for dispersion curve tracking in ocean acoustics

A particle filtering method is developed for dispersion curve extraction from spectrograms of broadband acoustic signals propagating in underwater media. The goal is to obtain accurate representation of modal dispersion which can be employed for source localization and geoacoustic inversion. Results are presented from the application of the method to synthetic data, demonstrating the potential of the approach for accurate estimation of waveguide dispersion characteristics. The method outperforms simple time-frequency analysis providing estimates that are very close to numerically calculated dispersion curves. The method also provides uncertainty information on modal arrival time estimates, typically unavailable when traditional methods are used.