Jorge E. Quijano

Bayesian geoacoustic inversion using wind-driven ambient noise.

This paper applies Bayesian inversion to bottom-loss data derived from wind-driven ambient noise measurements from a vertical line array to quantify the information content constraining seabed geoacoustic parameters. The inversion utilizes a previously proposed ray-based representation of the ambient noise field as a forward model for fast computations of bottom loss data for a layered seabed. This model considers the effect of the arrays finite aperture in the estimation of bottom loss and is extended to include the wind speed as the driving mechanism for the ambient noise field. The strength of this field relative to other unwanted noise mechanisms defines a signal-to-noise ratio, which is included in the inversion as a frequency-dependent parameter. The wind speed is found to have a strong impact on the resolution of seabed geoacoustic parameters as quantified by marginal probability distributions from Bayesian inversion of simulated data. The inversion method is also applied to experimental data collected at a moored vertical array during the MAPEX 2000 experiment, and the results are compared to those from previous active-source inversions and to core measurements at a nearby site.

Demonstration of the invariance principle for active sonar

Active sonar systems can provide good target detection potential but are limited in shallow water environments by the high level of reverberation produced by the interaction between the acoustic signal and the ocean bottom. The nature of the reverberation is highly variable and depends critically on the ocean and seabed properties, which are typically poorly known. This has motivated interest in techniques that are invariant to the environment. In passive sonar, a scalar parameter termed the waveguide invariant, has been introduced to describe the slope of striations observed in lofargrams. In this work, an invariant for active sonar is introduced. This active invariant is shown to be present in the time-frequency structure observed in sonar data from the Malta Plateau, and the structure agrees with results produced from normal mode simulations. The application of this feature in active tracking algorithms is discussed.

Enhanced Kalman Filter Algorithm Using the Invariance Principle

Target tracking in multistatic active sonar systems is often limited in shallow-water environments due to the high level of bottom reverberation that produces false detections. Past research has shown that these false alarms may be mitigated when complete knowledge of the environment is available for discrimination, but these methods are not robust to environmental uncertainty. Recent work has demonstrated the existence of a waveguide invariant for active sonar geometries. Since this parameter is independent of specifics of the environment, it may be used when the environment is poorly known. In this paper, the invariance extended Kalman filter (IEKF) is proposed as a new tracking algorithm that incorporates dynamic frequency information in the state vector and uses the invariance relation to improve tracker discrimination. IEKF performance is quantified with both simulated and experimental sonar data and results show that the IEKF tracks the target better than the conventional extended Kalman filter (CEKF) in the presence of false detections.

Trans-dimensional geoacoustic inversion of wind-driven ambient noise

This letter applies trans-dimensional Bayesian geoacoustic inversion to quantify the uncertainty due to model selection when inverting bottom-loss data derived from wind-driven ambient-noise measurements. A partition model is used to represent the seabed, in which the number of layers, their thicknesses, and acoustic parameters are unknowns to be determined from the data. Exploration of the parameter space is implemented using the Metropolis-Hastings algorithm with parallel tempering, whereas jumps between parameterizations are controlled by a reversible-jump Markov chain Monte Carlo algorithm. Sediment uncertainty profiles from inversion of simulated and experimental data are presented.

Experimental observations of active invariance striations in a tank environment

The waveguide invariant in shallow water environments has been widely studied in the context of passive sonar. The invariant provides a relationship between the frequency content of a moving broadband source and the distance to the receiver, and this relationship is not strongly affected by small perturbations in environment parameters such as sound speed or bottom features. Recent experiments in shallow water suggest that a similar range-frequency structure manifested as striations in the spectrogram exists for active sonar, and this property has the potential to enhance the performance of target tracking algorithms. Nevertheless, field experiments with active sonar have not been conclusive on how the invariant is affected by the scattering kernel of the target and the sonar configuration (monostatic vs bistatic). The experimental work presented in this paper addresses those issues by showing the active invariance for known scatterers under controlled conditions of bathymetry, sound speed profile and high SNR. Quantification of the results is achieved by introducing an automatic image processing approach inspired on the Hough transform for extraction of the invariant from spectrograms. Normal mode simulations are shown to be in agreement with the experimental results.

Extraction of time-frequency target features

Physics-based detection algorithms can improve discrimination of sonar targets from competing bottom reverberation, but are vulnerable to environmental uncertainties. Recent research in the underwater community has identified an environmentally robust time-frequency signature for improved target discrimination. Application of this “invariant” requires processing algorithms to identify striations in a spectrogram and to quantify the associated track certainty. In this paper, two robust invariant-based algorithms are presented and demonstrated with underwater data. The first algorithm uses a Kalman Filter to estimate the time-frequency striations in sonar spectrograms. The second computes a “likeliness” metric to measure discrimination between target and non-target detections.

Radiative transfer theory applied to ocean bottom modeling

Research on the propagation of acoustic waves in the ocean bottom sediment is of interest for active sonar applications such as target detection and remote sensing. The interaction of acoustic energy with the sea floor sublayers is usually modeled with techniques based on the full solution of the wave equation, which sometimes leads to mathematically intractable problems. An alternative way to model wave propagation in layered media containing random scatterers is the radiative transfer (RT) formulation, which is a well established technique in the electromagnetics community and is based on the principle of conservation of energy. In this paper, the RT equation is used to model the backscattering of acoustic energy from a layered elastic bottom sediment containing distributions of independent scatterers due to a constant single frequency excitation in the water column. It is shown that the RT formulation provides insight into the physical phenomena of scattering and conversion of energy between waves of different polarizations.

Use of the invariance principle for target tracking in active sonar geometries

The propagation of broadband acoustic waves in shallow water channels is a complicated phenomenon that depends critically on the attributes of the water column and bottom structure, and it is characterized by the interference between propagation modes. In the far field, multiple interactions of the acoustic wave with the boundaries of the channel result in signal attenuation and multipath propagation which makes the interpretation of sonar signals difficult. For the passive case, it has been shown that the time-frequency structure resulting from this propagation can be explained with the principle of a waveguide invariant and that this description does not require precise knowledge of the propagation environment. The invariance principle has been successfully applied to the interpretation of passive sonar lofargrams where the signal travels a single path between the source and the receiver, but little work has been done for active sonar applications in which the acoustic wave follows a bistatic path. In this paper, experimental results from the Shallow Water Active Detection/Classification (SWAC) project are presented. Frequency analysis of the acoustic data reveals the presence of striations similar to those found in passive sonar lofargrams and this suggests the existence of a bistatic invariance principle. Physics-based simulations using the measured sound speed profile are also presented and they are in agreement with the observed results. The identification of a bistatic invariance principle for active sonar could lead to the implementation of robust processing methods and simultaneously decrease the complexity of tracking algorithms by adding constraints in the search domain

Geoacoustic inversion for the seabed transition layer using a Bernstein polynomial model

This paper develops an inversion method for the seabed transition layer at the water-sediment interface, often found in muddy sediments, which provides density and sound-speed profiles that were previously not resolvable. The resolution improvements are achieved by introducing a parametrization that captures general depth-dependent gradients in geoacoustic parameters with a small number of parameters. In particular, the gradients are represented by a sum of Bernstein basis functions, weighted by unknown coefficients. Compared to previous forms found in the literature, the Bernstein-based parametrization can represent a wider range of depth-dependent geoacoustic profiles using fewer parameters which leads to reduced uncertainty and improved resolution. In addition, the Bernstein basis is the most stable polynomial representation in that small perturbations to the unknown coefficients result in small, localized perturbations to the geoacoustic profile, thereby providing an efficient exploration of the parameter space using Markov-chain methods in nonlinear inversion. Geoacoustic profiles at four mud sites on the Malta Plateau are studied with the proposed approach. Results show exceptional resolution of density profiles, estimated with low uncertainty and clear sensitivity to sediment features of centimeter scale.

Application of Radiative Transfer Theory to Acoustic Propagation in the Ocean Bottom

Acoustic scattering from the ocean bottom has been extensively studied by applying analytical methods based on the wave equation. This has the advantage of being mathematically rigorous but many of these techniques are not applicable for complex sediment environments with combined volume and rough surface scattering. In this research, the use of the radiative transfer (RT) theory is explored as a way to address layered ocean sediments with embedded scatterers in a computationally tractable manner. The RT formulation has been applied extensively in electromagnetic applications involving layered media and has been considered for acoustic waves with applications to ultrasound but has not previously been applied to acoustic scattering in ocean sediments. The RT theory uses principles of conservation of energy to describe the behavior of a wave propagating in a volume with random scatterers. Using this model, the non homogeneous volume can be characterized by emission and extinction coefficients which can be computed in closed form for scatterers such as elastic spheres, cavities or cylinders or by numerical methods or analytic approximations for more complex geometries. In this paper, an infinite half space of sand with embedded spherical cavities is considered. The Fresnel reflection/transmission coefficients are utilized to provide examples of the backscattered signal level that could be expected due to volume scattering. It is shown that for typical sandy sediments with small shear sound speed, the main contribution to the volume backscattering is due to longitudinal waves that couple from the sediment into the water column, while the coupling of vertical shear waves is weak.