Improvement of a Green's Function Estimation for a Moving Source Using the Waveguide Invariant Theory.

Understanding the characteristics of underwater sound channels is essential for various remote sensing applications. Typically, the time-domain Green's function or channel impulse response (CIR) is obtained using computationally intensive acoustic propagation models that rely on accurate environmental data, such as sound speed profiles and bathymetry. Ray-based blind deconvolution (RBD) offers a less computationally demanding alternative using plane-wave beamforming to estimate the Green's function.

Adaptive iterative transfer learning for effective snapping shrimp sound detection.

This study aims to detect the bioacoustics signal in the underwater soundscape, specifically those produced by snapping shrimp, using adaptive iterative transfer learning. The proposed network is initially trained with pre-classified snapping shrimp sounds and Gaussian noise, then applied to classify and remove snapping-free noise from field data. This separated ambient noise is subsequently used for transfer learning.

Source localization based on steered frequency-wavenumber analysis for sparse array.

When using a sparse array, locating the target signal of a high-frequency component is difficult. Although forecasting the direction in a sparse situation is challenging, the frequency-wavenumber (f-k) spectrum can simultaneously determine the direction and frequency of the analyzed signal. The striation of the f-k spectrum shifts along the wavenumber axis in a sparse situation, which reduces the spatial resolution required to determine the target's direction using the f-k spectrum.

Direction-of-Arrival Estimation Based on Frequency Difference-Wavenumber Analysis for Sparse Vertical Array Configuration.

Frequency-wavenumber (-) analysis can estimate the direction of arrival (DOA) of broadband signals received on a vertical array. When the vertical array configuration is sparse, it results in an aliasing error due to spatial sampling; thus, several striation patterns can emerge in the - domain. This paper extends the - analysis to a sparse receiver-array, wherein a multitude of sidelobes prevent resolving the DOA estimates due to spatial aliasing.

An overview of array invariant for source-range estimation in shallow water.

Traditional matched-field processing (MFP) refers to array processing algorithms, which fully exploit the physics of wave propagation to localize underwater acoustic sources. As a generalization of plane wave beamforming, the "steering vectors," or replicas, are solutions of the wave equation descriptive of the ocean environment. Thus, model-based MFP is inherently sensitive to environmental mismatch, motivating the development of robust methods.

The waveguide invariant for a Pekeris waveguide.

A closed-form waveguide invariant β for a Pekeris waveguide is derived. It is based on the modal Wentzel-Kramers-Brillouin (WKB) dispersion equation and implicit differentiation, in conjunction with the concept of the "effective boundary depth," ΔH(θ), where θ is the propagation angle. First, an explicit formula for β(m,n) between mode pairs is obtained assuming an ideal waveguide of the effective waveguide depth, H+ΔH(θ), and provides an excellent agreement with the reference value for the Pekeris waveguide of depth H obtained using the normal mode program kraken.

Localization of a distant ship using a guide ship and a vertical array.

A method is presented for estimating the range of a distant ship in shallow water using a vertical array and a guide ship at a known range close to the array. The method involves a combination of four different approaches: blind deconvolution, waveguide invariant, virtual receiver (VR), and array invariant. (1) Blind deconvolution extracts a time-domain Green's function from the broadband acoustic source (guide ship).

Adaptive array invariant in range-dependent environments with variable bathymetry.

The adaptive array invariant developed for source-range estimation in shallow water can incorporate the propagation-angle dependence of the waveguide invariant for an ideal waveguide (β=cosθ) [Byun and Song, J. Acoust. Soc.

Extracting Green's functions between ships of opportunity using a vertical array.

A theoretical method for estimating the Green's function between two points in an acoustic waveguide was proposed using a vertical source array that spans sufficient waveguide depth [Roux and Fink, J. Acoust. Soc.

Adaptive array invariant.

The array invariant (χ) developed for robust source-range estimation in shallow water is based on the broadband dispersion characteristics in ideal waveguides that can be summarized by the waveguide invariant, β=cosθ, with propagation angle θ. The standard array invariant relies on the waveguide invariant being constant, e.g.

Extrapolating Green's functions using the waveguide invariant theory.

The broadband interference structure of sound propagation in a waveguide can be described by the waveguide invariant, β, that manifests itself as striations in the frequency-range plane. At any given range (r), there is a striation pattern in frequency (ω), which is the Fourier transform of the multipath impulse response (or Green's function). Moving to a different range (r+Δr), the same pattern is retained but is either stretched or shrunken in ω in proportion to Δr, according to Δω/ω=β(Δr/r).

Multiple constraint matched field processing tolerant to array tilt mismatch.

A multiple constraint method (MCM) specifically designed to accommodate the uncertainty of array tilt is developed for matched field processing (MFP). Combining the MCM with the white noise gain constraint method results in a processor that is tolerant to both array tilt and environmental mismatch. Experimental results verify the robustness of the proposed MFP to localize and track a surface ship radiating broadband noise (200-500 Hz), using a 56-m long vertical array with tilt in approximately 100-m deep shallow water.

Localization of multiple ships using a vertical array in shallow water.

The blind deconvolution employs conventional plane-wave beamforming using an array, selects a well-resolved angle of arrival for beam steering to estimate the phase component of an unknown source waveform, and then extracts the Green's function between the source and the array. In this letter, the approach is extended to multiple-ship scenarios in which the multipath arrivals from one ship are masked by other ships, adopting the basic concept of successive interference cancellation. Once individual Green's functions are available, the array invariant method based on the beam-time migration can be subsequently applied to estimate each source range.

Remote acoustic illumination using time reversal and a surface ship.

Time-reversal (TR) transmission of the Green's function between a time-reversal mirror (TRM) and a probe source (PS) in an acoustic waveguide produces a spatio-temporal focus at the PS location. The TR focus then behaves as a virtual point source in the outbound direction with respect to the TRM. Further, a collection of adjacent TR focuses may constitute a virtual source array (VSA) that can serve as a remote platform, redirecting the focused field to a selected location beyond the VSA for which the Green's function is not available a priori.

Ray-based blind deconvolution of shipping sources using multiple beams separated by alternating projection.

This article presents a method for improving the performance of the ray-based blind deconvolution (RBD) algorithm, which was first proposed by Sabra, Song, and Dowling [J. Acoust. Soc.

Performance comparisons of array invariant and matched field processing using broadband ship noise and a tilted vertical array.

This paper compares the localization performance of array invariant (AI) and matched field processing (MFP) using a ship of opportunity radiating random noise (200-900 Hz) and a tilted vertical array. AI is a deterministic approach to source-range estimation (i.e.

Simultaneous localization of a surface ship and a submerged towed source (L).

The cascade of blind deconvolution and array invariant has been successful for localizing a single source, either a surface ship or a submerged source, using a vertical array without knowledge of the environment or source waveform in shallow water. In this letter, the blind deconvolution is extended to a two-source case where individual Green's functions are separately extracted by exploiting a distinct group of modes strongly excited at different source depths. The subsequent array invariant confirms that a surface ship and a towed source at 50-m depth can be simultaneously localized using a 56-m long vertical array in 100-m deep shallow water.

Real-time tracking of a surface ship using a bottom-mounted horizontal array.

The cascade of blind deconvolution and array invariant has been successful to localize and track a surface ship radiating random waveforms, using a 56-m long vertical array in 100-m deep shallow water. In this paper, it is shown that a 60-m long, bottom-mounted horizontal array can be utilized for blind deconvolution to extract the Green's functions from the same ship (100-800 Hz), in conjunction with the array invariant for source-range estimation. The additional information obtained with a horizontal array is the source bearing (azimuth angle, ) from the well-resolved ray angle identified for blind deconvolution to extract the phase component of the unknown source waveforms.

Array invariant-based calibration of array tilt using a source of opportunity.

The array invariant, a robust approach to source-range estimation in shallow water, is based on the dispersion characteristics of broadband signals in ideal waveguides. It involves time-domain plane-wave beamforming using a vertical line array (VLA) to separate multiple coherent arrivals in beam angle and travel time. Typically, a probe signal (i.

Array invariant-based ranging of a source of opportunity.

The feasibility of tracking a ship radiating random and anisotropic noise is investigated using ray-based blind deconvolution (RBD) and array invariant (AI) with a vertical array in shallow water. This work is motivated by a recent report [Byun, Verlinden, and Sabra, J. Acoust.

Cascade of blind deconvolution and array invariant for robust source-range estimation.

The array invariant proposed for robust source localization in shallow water is based on the dispersion characteristics in ideal waveguides. It involves conventional plane-wave beamforming using a vertical array, exploiting multiple arrivals separated in beam angle and travel time, i.e.