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An acoustic propagation model is applied to predict measurements of three-dimensional (3-D) effects recorded off the southeast coast of Florida. The measured signal is produced by a low frequency source that is towed north parallel to the shelf from a fixed receiving array. The acoustic data show the direct path arrival at the bearing of the tow ship and a second refracted path arrival as much as 30° inshore of the direct arrival. Notably, the refracted arrival has a received level more than 25 dB greater than that of the direct arrival. A geoacoustic model of the environment is created to explain the data. It is shown that the topography of the seafloor plays the largest role in controlling horizontal refraction effects, whereas the range-dependent sediment properties have the most influence on the received level. The modeling approach is based on a 3-D adiabatic mode technique in which the horizontal refraction equation is solved using a parabolic equation in Cartesian coordinates. A modal decomposition of the field provides insight into the variability in the arrival angle and received level of the measured signal.

This paper presents results of a range-independent perturbative inverse approach applied to data from the Shallow Water Experiment 2006. The inversion technique is based on a linearized relationship between sound speed in the sediment and modal eigenvalues. Horizontal wave numbers were estimated from data collected from two distinct source/receiver tracks oriented along and across the shelf. The specific inversion algorithm used is based on qualitative regularization and uses known information about the environment to constrain the solution. Locations of the R reflector and other layering information are used as a priori information for the inversion to emphasize the layered structure of the sediment.

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The Pacific Arctic Region has experienced decadal changes in atmospheric conditions, seasonal sea-ice coverage, and thermohaline structure that have consequences for underwater sound propagation. To better understand Arctic acoustics, a set of experiments known as the deep-water Canada Basin acoustic propagation experiment and the shallow-water Canada Basin acoustic propagation experiment was conducted in the Canada Basin and on the Chukchi Shelf from summer 2016 to summer 2017. During the experiments, low-frequency signals from five tomographic sources located in the deep basin were recorded by an array of hydrophones located on the shelf. Over the course of the yearlong experiment, the surface conditions transitioned from completely open water to fully ice-covered. The propagation conditions in the deep basin were dominated by a subsurface duct; however, over the slope and shelf, the duct was seen to significantly weaken during the winter and spring. The combination of these surface and subsurface conditions led to changes in the received level of the sources that exceeded 60 dB and showed a distinct spacio-temporal dependence, which was correlated with the locations of the sources in the basin. This paper seeks to quantify the observed variability in the received signals through propagation modeling using spatially sparse environmental measurements.

The environment of the New Jersey shelf is characterized by high spatial and temporal variability of water column properties caused by intrusions of warm, salty water from the continental slope. These intrusions cause fluctuations in the water column sound speed profile which can have significant effects on acoustic propagation in shallow water. In this work, a linearized perturbative inverse technique is applied to estimate range-dependent water column sound speed profiles. This method utilizes estimates of horizontal wave numbers to determine sound speed as a function of depth. This technique is appropriate for the range-dependent shallow-water environment as horizontal wave numbers can be measured semilocally (1-2 km aperture) and their values are a direct measurement of the local environmental parameters. Difficulty is encountered in application of the perturbative inverse technique because the wave number data are insensitive to some portions of the waveguide and, as a result, the solution can deviate wildly from true values. This issue is addressed by application of approximate equality constraints which force the solution to be close to likely values at prescribed locations.

A geoacoustic inversion scheme to estimate the depth-dependent sound speed characteristics of the shallow-water waveguide is presented. The approach is based on the linearized perturbative technique developed by Rajan et al. [J. Acoust. Soc. Am. 82, 998-1017 (1987)]. This method is applied by assuming a background starting model for the environment that includes both the water column and the seabed. Typically, the water column properties are assumed to be known and held fixed in the inversion. Successful application of the perturbative inverse technique lies in handling issues of stability and uniqueness associated with solving a discrete ill-posed problem. Conventionally, such problems are regularized, a procedure which results in a smooth solution. Past applications of this inverse technique have been restricted to cases for which the water column sound speed profile was known and sound speed in the seabed could be approximated by a smooth profile. In this work, constraints that are better suited to specific aspects of the geoacoustic inverse problem are applied. These techniques expand on the original application of the perturbative inverse technique by including the water column sound speed profile in the solution and by allowing for discontinuities in the seabed sound speed profile.

Estimates of the spatial and temporal variability of ocean sound speed on the New Jersey shelf were obtained using acoustic signals measured by a set of freely drifting buoys. The range- and time-dependent inversion problem is computationally intensive and a linearized perturbative algorithm was applied to obtain results in an efficient manner. The inversion algorithm uses estimates of modal travel time to determine sound speed as a function of range and depth. In order to handle the high volume of data associated with the acoustic sensing network, the modal travel time estimation process was automated using an adaptive time-frequency signal processing method known as time-warping. Time-warping is a model-based transform that converts the frequency-dependent modal arrivals to monotones in the warped domain where they can be easily filtered. The data analyzed in this paper were collected on 16 March 2011 on the New Jersey shelf when the ocean was relatively well-mixed. While the observed sound-speed variations are small, both spatial and temporal trends are observed in the results. Furthermore, the estimated sound-speed profiles show good agreement with temporally and spatially collocated measurements.