Modeling Acoustic Scattering from the Seabed Using Transport Theory

Radiative Transfer (RT) theory has established itself as an important tool for electromagnetic remote sensing in parallel plane geometries with random distributions of scatterers, and most recently it has also been proposed as a model for the propagation of elastic waves in layered ocean sediments. In this work the capabilities of this model are illustrated, as the RT method is used to predict backscattering strength from laboratory models of random media. The RT model is characterized by its flexibility on accommodating scatterers in a broad variety of sizes, shapes, and acoustic contrast relative to the background media. Additionally, this formulation is easily expandable to include multiple layering and elastic effects. In this paper, a comparison between the RT model and the results from two laboratory experiments in the optics and the Mie regime are presented. The experiments were designed to measure volume scattering at high frequencies between 280 kHz and 400 kHz in monostatic configuration. The first experiment used large aluminum spheres suspended with thin filaments, and it serves as a benchmark for testing the RT formulation due to its high signal-to-noise ratio, and the absence of reflective boundaries or background attenuation. Measurements of frequency dependent backscattering at normal incidence angle are shown for two fractional volumes. For the second experiment, the scattering media is a well characterized slab of a lossy resin background containing a uniform distribution of glass beads, and angle- and frequency-dependent measurements are presented. The levels of volume scattering from both experiments are found in agreement with predictions from the steady state RT model

Depth-Based Signal Separation with Vertical Line Arrays in the Deep Ocean

Deep vertical line arrays can exploit the reliable acoustic path (RAP), which provides low transmission loss (TL) for targets at moderate ranges, and increased TL for distant interferers. However, nearby surface interference also has favorable RAP propagation and cannot be separated from a submerged target without horizontal aperture. In this work, a physics-based Fourier transform variant is introduced, which achieves depth-based signal separation by exploiting the spatial structure resulting from the coherent addition of the direct and surface-reflected propagation paths present for submerged sources. Simulation results demonstrate depth-based signal separation without requiring knowledge of the ocean environment

Striation-Based Beamforming for Estimating the Waveguide Invariant with Passive Sonar

The waveguide invariant summarizes the pattern of constructive and destructive interference between acoustic modes propagating in the ocean waveguide. For many sonar signal-processing schemes, it is essential to know the correct numerical value for the waveguide invariant. While conventional beamforming can estimate the ratio between the waveguide invariant and the range to the source, it cannot unambiguously separate the two terms. In the present work, striationbased beamforming is developed. It is shown that the striation-based beamformer can be used to produce an estimate for the waveguide invariant that is independent of the range. Simulation results are presented

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

Source motion mitigation for adaptive matched field processing

Application of adaptive matched field processing to the problem of detecting quiet targets in shallow water is complicated by source motion, both the motion of the target and the motion of discrete interferers. Target motion causes spreading of the target peak, thereby reducing output signal power. Interferer motion increases the dimensionality of the interference subspace, reducing adaptive interference suppression. This paper presents three techniques that mitigate source motion problems in adaptive matched field processing. The first involves rank reduction, which enables adaptive weight computation over short observation intervals where motion effects are less pronounced. The other two techniques specifically compensate for source motion. Explicit target motion compensation reduces target motion mismatch by focusing snapshots according to a target velocity hypothesis. And time-varying interference filtering places time-varying nulls on moving interferers not otherwise suppressed by adaptive weights. The three techniques are applied to volumetric array data from the Santa Barbara Channel Experiment and are shown to improve output signal-to-background-plus-noise ratio by more than 3 dB over the standard minimum-variance, distortionless response adaptive beam-former. Application of the techniques in some cases proves to be the difference between detecting and not detecting the target

Extraction of Small Boat Harmonic Signatures from Passive Sonar

This paper investigates the extraction of acoustic signatures from small boats using a passive sonar system. Noise radiated from a small boats consists of broadband noise and harmonically related tones that correspond to engine and propeller specifications. A signal processing method to automatically extract the harmonic structure of noise radiated from small boats is developed. The Harmonic Extraction and Analysis Tool (HEAT) estimates the instantaneous fundamental frequency of the harmonic tones, refines the fundamental frequency estimate using a Kalman filter, and automatically extracts the amplitudes of the harmonic tonals to generate a harmonic signature for the boat. Results are presented that show the HEAT algorithms ability to extract these signatures

Automated Extraction and Classification of Time-Frequency Contours in Humpback Vocalizations

A time-frequency contour extraction and classification algorithm was created to analyze humpback whale vocalizations. The algorithm automatically extracted contours of whale vocalization units by searching for gray-level discontinuities in the spectrogram images. The unit-to-unit similarity was quantified by cross-correlating the contour lines. A library of distinctive humpback units was then generated by applying an unsupervised, cluster-based learning algorithm. The purpose of this study was to provide a fast and automated feature selection tool to describe the vocal signatures of animal groups. This approach could benefit a variety of applications such as species description, identification, and evolution of song structures. The algorithm was tested on humpback whale song data recorded at various locations in Hawaii from 2002 to 2003. Results presented in this paper showed low probability of false alarm (0%–4%) under noisy environments with small boat vessels and snapping shrimp. The classification algorithm was tested on a controlled set of 30 units forming six unit types, and all the units were correctly classified. In a case study on humpback data collected in the Auau Chanel, Hawaii, in 2002, the algorithm extracted 951 units, which were classified into 12 distinctive types

Propuesta de un rediseño organizacional para la Corporación O'Globo SAC de la ciudad de Chiclayo

La presente investigación tuvo como objetivo proponer un rediseño organizacional para la editorial Corporación O’Globo SAC de la ciudad de Chiclayo, con la finalidad de mejorar las operaciones que viene desarrollando actualmente. Esta propuesta se inició con la recopilación de información a través de entrevistas a profundidad tanto al gerente general, como demás trabajadores de la empresa, para detectar los focos problemáticos dentro de ella. Así mismo se analizó su entorno de forma global, mediante la matriz SEPTE y FODA, las cinco fuerzas de Porter, documentos de gestión y cultura organizacional, generando un impacto positivo en la comprensión y desarrollo de la investigación. En el análisis de la información se detectó que la empresa no cuenta con una estructura organizacional definida, mucho menos con una planificación adecuada, revelando el accionar empírico de sus trabajadores; lo que se ve reflejado en la escasa gestión administrativa. Al concluir la investigación se propone un organigrama donde se visualice la organización de áreas administrativas, mapeo de procesos y se presentan los documentos de gestión para la Corporación O’Globo SAC.Tesi

An Eigenvector-Based Test for Local Stationarity Applied to Array Processing

In sonar array processing, a challenging problem is the estimation of the data covariance matrix in the presence of moving targets in the water column, since the time interval of data local stationarity is limited. This work describes an eigenvector-based method for proper data segmentation into intervals that exhibit local stationarity, providing data-driven higher bounds for the number of snapshots available for computation of time-varying sample covariance matrices. Application of the test is illustrated with simulated data in a horizontal array for the detection of a quiet source in the presence of a loud interferer

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