In the ocean, light from the surface dissipates quickly leaving sound the only way to see at a distance. Different sediment types on the ocean floor and water properties like salinity, temperature, and ocean depth all change how sound travels across long distances. Hard sediment types, such as sand and bedrock, are highly reflective while softer sediment types, such as mud, are more absorptive and change the received sound upon arrival. Unfortunately, the vast majority of the ocean floor is not mapped and the expenses involved in creating such a map are far too great. Traditional signal processing methods in underwater acoustics attempt to localize sources and estimate seabed properties, but require a priori decisions and fall victim to ill conditioning and non-linear relationships between the unknowns and are computationally expensive. To address these problems, a deep learning method is proposed to distinguish between seabed types while also predicting source parameters such as source-receiver range from simulated training data. In this thesis, several studies are presented that explore the effectiveness of convolutional neural networks to make predictions from two types of sounds that propagated through the ocean: impulsive explosions and ship noise. These studies show that time-series signals and spectrograms contain sufficient information for deep learning, and additional preprocessing for feature extraction is not necessary. Training data considerations, such as randomness in the network weights and inclusion of representative variability are also explored. In all, this study shows that deep learning is a useful tool in underwater acoustics and has significant potential for seabed parameter estimation.

Vertical line arrays (VLAs) deployed below the critical depth in the deep ocean can exploit reliable acoustic path (RAP) propagation, which provides low transmission loss (TL) for targets at moderate ranges, and increased TL for distant interferers. However, sound from nearby surface interferers also undergoes RAP propagation, and without horizontal aperture, a VLA cannot separate these interferers from submerged targets. A recent publication by McCargar and Zurk (2013) addressed this issue, presenting a transform-based method for passive, depth-based separation of signals received on deep VLAs based on the depth-dependent modulation caused by the interference between the direct and surface-reflected acoustic arrivals. This thesis expands on that work by quantifying the transform-based depth estimation method performance in terms of the resolution and ambiguity in the depth estimate. Then, the depth discrimination performance is quantified in terms of the number of VLA elements.

Thesis (S.M.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 99-100). / Signal detection and synchronization in the time varying ocean environment is a difficult endeavor. The current common methods include using a linear frequency modulated chirped pulse or maximal length sequence as a detection pulse, then match filtering to that signal. In higher signal to noise ratio (SNR) environments (- 0 dB and higher) this has been a suitable solution. As the SNR drops lower however, this solution no longer provides an acceptable probability of detection for a given tolerable probability of false alarm. The issue derives from the inherent coherence issues in the ocean environment which limit the useful matched filter length. This thesis proposes an alternative method of detection based on a recursive least squares linearly adaptive equalizer which we term the Adaptive Linear Equalizer Detector (ALED). This detectors performance has demonstrated reliable probability of detection with minimal interfering false alarms with SNR as low as -20 dB. Additionally this thesis puts forth a computationally feasible method for implementing the detector. / by Ryan Thomas Gieleghem. / S.M.

The purpose of this report is to investigate the processing of tracking data for acoustic targets. The programs developed for two- and three- dimensional space calculate the target's position via "hyperbolic-fix" navigation (geometric) considerations using the Newton-Raphson algorithm. The computer programs and the tracking solution approach contained herein is based on knowledge of only the sensors' locations and the relative time-difference at which a target's referenced, singular, acoustic pressure wavefronts are received at the sensors. Omnidirectional sensors are found to be sufficient for the two-dimensional space tracking problem. However, it is found that the three-space problem required usage of directional frequency and ranging (DIFAR) sensors. Line printer plots are provided for the target position solutions; also; tabular track position solutions are provided.

This report proposes a novel technique for measuring of acoustic fields in water. A Laser Hydrophone is proposed taking advantage of the properties of Total Internal Reflection. A theoretical analysis of the idea is presented followed by a prediction of the operating characteristics of an actual system. Actual data were taken with the proposed system and it is compared to the predicted.

Approved for public release, distribution is unlimited / Continuing U.S. Navy interest in the development of light-weight, low-volume, broadband, underwater acoustic projectors and receivers is the principal motivation for this research topic. Acoustic cymbal transducers, so named for their geometric similarity to the percussion instruments, are miniature "class V" flextensional transducers that consist of a piezoelectric ceramic drive element bonded to two opposing cymbal-shaped metal shells. Operating as mechanical transformers, the two metal shells convert the naturally large generative force of a piezoelectric ceramic in the radial mode into increased volume displacement at the metal shell surface to obtain usable source levels and sensitivities in a broad frequency range. The magnified displacement makes the acoustic cymbal element a potential alternative to acoustic transduction technologies presently used to generate and receive Navy sonar frequencies. Potential benefits to utilizing this technology are generating or receiving broadband sound, at sonar frequencies in a thin, low volume, conformable package. Applications of this technology have been limited because air-backed acoustic cymbal elements undergo degradation in performance when exposed to elevated hydrostatic pressure (i.e., deep ocean and extreme littoral water applications). This research shows that consistent and reliable acoustic performance can be achieved with cymbal-based transducers at hydrostatic pressures of interest to the Navy. / Civilian, United States Navy

published_or_final_version / Physics / Doctoral / Doctor of Philosophy

Approved for public release, distribution is unlimited / A recent improvement to the Seaweb underwater wireless network was the implementation of a Selective Automatic Repeat Request (SRQ) mechanism. SRQ is a protocol implemented in the Seaweb link layer as a measure for mitigating unreliability inherent in the telesonar physical layer. In January 2004, an experiment was performed in St. Andrew's Bay, Panama City, Florida. The goal was to transmit large data files through the network, in accordance with a Naval Special Warfare need for imagery file telemetry. For three point-to-point test geometries, SRQ was tested with a noisy and variable physical layer. Through the incorporation of SRQ, the unreliability was overcome. A link-budget model calibrated with the sound channel data collected from the experiment establishes the benefit of a "SRQ gain." / Ensign, United States Navy

Passive acoustic monitoring has been used to investigate many aspects of marine mammal ecology, although methods to estimate absolute abundance and density using acoustic data have only been developed in recent years. The instrument configuration in an acoustic survey determines which abundance estimation methods can be used. Sparsely distributed arrays of instruments are useful because wide geographic areas can be covered. However, instrument spacing in sparse arrays is such that the same vocalisation will not be detected on multiple instruments, excluding the use of some abundance estimation methods. The aim of this thesis was to explore cetacean abundance and density estimation using novel sparse array datasets, applying existing methods where possible, or developing new approaches. The wealth of data collected by sparse arrays was demonstrated by analysing a 10-year dataset collected by the U.S. Navy's Sound Surveillance System in the north-east Atlantic. Spatial and temporal patterns of blue (Balaenoptera musculus) and fin whale (Balaenoptera physalus) vocal activity were investigated using generalised additive models. Distance sampling-based methods were applied to fin whale calls recorded by an array of Ocean Bottom Seismometers in the north-east Atlantic. Estimated call density was 993 calls/1000 km².hr⁻¹ (CV: 0.39). Animal density could not be estimated because the call rate was unknown. Further development of the call localisation method is required so the current density estimate may be biased. Furthermore, analysing a single day of data resulted in a high variance estimate. Finally, a new simulation-based method developed to estimate density from single hydrophones was applied to blue whale calls recorded in the northern Indian Ocean. Estimated call density was 3 calls/1000 km².hr⁻¹ (CV: 0.17). Again, density of whales could not be estimated as the vocalisation rate was unknown. Lack of biological knowledge poses the greatest limitation to abundance and density estimation using acoustic data.

In June 2003, the Littoral Acoustic Demonstration Center conducted an acoustic characterization experiment for a standard seismic exploration array. Two moorings with Environmental Acoustic Recording Systems (EARS) were deployed in the northern part of the Gulf of Mexico to measure ambient noise and collect shot information. A 21-element seismic airgun array was towed along five parallel linear tracks with horizontal closest approach points to the EARS buoy position of 63, 500, 1000, 2000, and 5000 m. Calibrated acoustic pressure measurements collected during the experiment were analyzed to obtain zero-to-peak sound pressures, sound exposure levels, and pressure levels in 1/3-octave frequency bands. In addition, the experimental data were modeled by using a modified underwater acoustic propagation model to fill in missing data measurements. The resulting modeling procedure showed good agreement between measured and modeled data in absolute pressure amplitudes and frequency interference patterns for frequencies up to 1000 Hz. The analysis is important for investigating the potential impact on marine mammals and fish and predicting the exposure levels for newly planned seismic surveys in other geographic areas. Based on results of the experiment conducted and data analysis performed, a new experimental design was proposed to maximize the amount of collected data using the available equipment while minimizing the time needed for the source ship. The design used three patches, one with 3º angular spacing between the lines at a reference depth. Embedded is a smaller patch with 1º spacing and within that a still smaller patch with one half degree spacing. This arrangement gives a reasonably uniform distribution of shots versus solid angle with a large variety of emission and azimuthal angles for different ranges. Due to the uncertainty of positioning systems, the angular space is divided into solid angle bins. Simulations predicted more than 200 shots per bin for emission angles greater than 13 degrees. Statistical analysis of collected data will be performed on the proposed bin basis. An experiment based on the proposed design was conducted in Fall 2007. The data measurements collected during the experiment are currently being analyzed and will be reported in the near future.