Search

The Acoustic Laboratory for Marine Applications (ALMA) is a deployable and autonomous acoustic system, designed by DGA Naval Systems, to address problems in underwater acoustics, such as sound propagation in fluctuating environments. In this article, data from the ALMA-2016 at-sea campaign are used to analyze the ocean fluctuation's influence on sound propagation in a shallow-water waveguide. The experiment took place on the continental shelf of the island of Corsica in November 2016. A source and a receiver array were 9.3 km apart in a nearly constant water depth of 100 m. The source emitted a variety of signals from which the chirp (1–13 kHz) is used to extract the waveguide eigenrays. To do so, a time-domain beamforming is performed on the match-filtered received signals with an automatic detection of local maxima in the time of arrival/direction of arrival (TOA/DOA) domain. A 2 min acquisition period of more than 13 h duration shows significant fluctuations in eigenray TOAs/DOAs. Qualitative comparisons with synthetic signals obtained from simulations in two and three dimensions permit reproduction of the observed eigenray fluctuations without including range dependence of the sound-speed profile.

Marine traffic is an important noise contributor to the underwater soundscape. In addition to the growing marine traffic worldwide, the increase in both ship size and ship power tends to intensify the radiated noise, and thus the low-frequency noise level. Studies have shown that marine species can be impacted by the rapid growth of ambient noise levels. In particular, masking of communication or behavior changes in relation to noise exposure have been documented.Shipping noise and its consequences on marine fauna are now monitored, and their evolution is of major concern for marine policies. Shipping noise modeling, based on Automatic Identification System (AIS) data is the most common approach to providing underwater noise levels at basin scales. Indeed, most ships are equipped with AIS transmitters, sending information concerning both the ship (ID, activity, length, etc.) and its navigation (position, speed, heading, etc.). This information is used to compute traffic density maps, and to model the ship’s radiated noise. The ambient noise is finally inferred by propagating noise sources in the environment.In France, a first Covid-19 lockdown occurred from the 17th of March to the 11th of May 2020, reducing significantly the marine traffic. In particular, cruise ships, passenger vessels, vehicle carriers and containerships harbor callings have decreased by 27%, 13%, 7% and 2 % respectively in member states harbors from 2019 to 2020, according to the European Maritime Safety Agency (EMSA). This traffic decrease affected only specific categories of ships, and contributed to some extent to a decrease of the anthropogenic underwater noise.This study aims to analyze the impact of the traffic density reduction due to the lockdown on the shipping noise in the occidental part of the Mediterranean Sea by use of AIS datasets from 2019 and 2020, and eventually to discuss the potential benefit of traffic density reduction as a mitigation measure.

Numerical models are currently used to understand how environmental fluctuations impact acoustic propagation. Such a process can be tedious in complex fluctuating environments. This letter proposes a complementary approach based upon canonical correlation analysis (CCA) to determine statistical relationships between two sets of observed acoustic and oceanographic variables. It is shown, as an example, how CCA puts forward the impact of external and internal tide on shallow water propagation. Results are consistent with the physical understanding of tide impact on acoustic propagation. They encourage the use of CCA for complex studies, in particular, for environments fluctuating under several environmental phenomena.

Maps of underwater noise generated by shipping activity became a useful tool to support international regulations on marine environments. They are used to infer the risk of impact on biodiversity. Maps are performed by 1) computing the emitted noise levels from ships, 2) propagating the acoustic signal in the environment and 3) using localized measurements to validate the results. Because of mismatches in environmental data and a limited number of measurements, noise maps remain highly uncertain.In this work, the uncertainty of the noise maps is investigated through the potential complexity of soundscape. The acoustic signal at each receiving cell is computed from the convolution of the source of the ships by the transmission losses of the environment. Complexity is mapped by computing Shannon's entropy of the transmission losses for each receiver. High entropy areas only reflect high shipping densities and favorable acoustic propagation properties of the local environment. Low entropy areas reflect: low shipping density and/or poor acoustic propagation properties. An area with high shipping densities and poor acoustic propagation properties will still have low entropy values.Entropy maps allow classifying areas depending on their environmental features. Thus, scenarios of uncertainty are defined. Results highlight the necessity to consider the diversity of the environmental properties in support of the production of noise maps. The methodology could help in optimizing spatial and temporal resolution of map computations, as well as optimizing acoustic monitoring strategies.

Underwater noise pollution from impulsive sources (e.g. explosions, seismic airguns, percussive pile driving) can affect marine fauna through mortality, physical injury, auditory damage, physiological stress, acoustic masking, and behavioural responses. Given the potential for large-scale impact on marine ecosystems, some countries are now monitoring impulsive noise activity, coordinated internationally through Regional Seas Conventions. Here, we assess impulsive noise activity in the Northeast Atlantic reported during 2015–2017 to the first international impulsive noise register (INR), established in 2016 under the OSPAR Convention. Seismic airgun surveys were the dominant noise source (38%–56% of annual activity) and declined by 23% during 2015–2017. Reported pile driving activity increased 72%. Explosions and sonar/acoustic deterrent devices both had year-on-year increases in reported activity. Some increases were attributable to more comprehensive reporting in later years. We discuss utilising the INR for risk assessment, target setting, and forward planning, and the implementation of similar systems in other regions.

With the aim of model and predict the underwater noise generated by the shipping traffic, the assessment of the traffic density is adopted in this study. This assessment is realised by using AIS data sets, where each AIS includes vessel name, details, location, speed, among other information. In order to analyse the influence of the comprehensiveness of AIS data sets on the modeled underwater noise, different AIS data sets are considered in this study. The results reveal that traffic noise modelling is strongly degraded by a lack of AIS positions, and data fusion as well as vessel pattern knowledge are greatly suggested to fill these lacks.

International audience; Thanks to its easy implementation and robust performance, beamforming is applied for source localisation in several fields. Its effectiveness depends greatly on the array sensor configuration. This paper introduces a criterion to improve the array beampattern and increase the accuracy of sound source localisation. The beamwidth and the maximum sidelobe level are used to quantify the spatial variation of the beampattern through a new criterion. This criterion is shown to be useful, especially for the localisation of moving sources. A genetic algorithm is proposed for the optimisation of microphone placement. Statistical analysis of the optimised arrays provides original results on the algorithm performance and on the optimal microphone placement. An optimised array is tested to localise the sound sources of a high speed train. The results show an accurate separation.

Underwater soundscape may be seen as an intrinsic feature of the environment in which it is recorded. In fact, underwater soundscape is a complex combination of sounds from a variety of acoustic sources, whether from natural or from human origin. When the distances between the sources and the receivers are sufficiently large, the received signals are strongly modified by the acoustic response of a continuously fluctuating marine environment. Then, spatio-temporal characteristics of the environment can be inferred from the measurements of soundscapes from hydrophone networks. The presentation aims to assess the spatial and temporal coherences of low frequency underwater ambient noise in the Indian Ocean basin. The data under consideration combine year round acoustic recordings from two recoding systems: on the one hand, data were from ~50 Ocean Bottom Seismometers (OBS) arranged in a network as large as 2000 km x 2000 km (http://www.rhum-rum.net/); and on the other hand acoustic data from hydrophones in the SOFAR channel.

International audience; In shallow water zones and at low frequency, seabed and water column properties can be estimated from the acoustic wavenumbers using inversion algorithms. When considering horizontal line arrays (HLA) and narrowband sources, the wavenumbers can be evaluated with classic spectral analysis methods. In this paper, a compressed sensing (CS) method for sparse recovery of the wavenumbers is proposed. This takes advantage of the few propagating modes and allows for spectral estimation when short HLA are used. The CS representation improves the wavenumber estimation, compared to the Fourier transform. However, for small arrays and several propagating modes, the CS generates interferences and does not allow proper wavenumber estimation. When considering broadband sources, it is possible to combine the wavenumbers estimated at several frequencies in order to build a frequency-wavenumber (f − k) representation. In this case, a post-processing tracking operation which improves the f − k resolution is presented. This relies on a general approach of waveguide physics and uses a particle filtering (PF) algorithm to track the wavenumbers. The consecutive use of CS and PF leads to a better wavenumber estimation. This methodology can be used for sources that are not at an end-fire position. It is illustrated by simulations and successfully applied on the Shallow Water 2006 data using the 32 sensor SHARK array.

The management of underwater noise within the European Union's waters is a significant component (Descriptor 11) of the Marine Strategy Framework Directive (MSFD). The indicator related to continuous noise, is the noise levels in two one-third octave bands centered at 63Hz and 125Hz. This paper presents an analysis of underwater noise in the Celtic Sea, a heavy shipping area which also hosts the seasonal Ushant thermal front. In addition to the MSFD recommended frequency bands, the analysis was extended to lower and upper frequency bands. Temporal and spatial variations as well as the influence of the properties of the water column on the noise levels were assessed. The noise levels in the area had a high dynamic range and generally exceeded 100dB re 1μPa. Finally, the results highlighted that oceanic mooring must be designed to minimize the pseudo-noise and consider the water column physical properties.

Shipping noise has been identified as a threat on underwater ecosystems. In particular, several impacts have been documented on cetaceans, e.g., communication’s masking and stress increasing. To assess the risk related to such anthropogenic noise requires both quantifying the noise levels and estimating the distribution of the cetaceans’ population. However, current methods evaluating the risks related to anthropogenic pressures generally rely on strong expert priors, which may be difficult to define. This presentation aims at introducing a new framework for the comparison of anthropogenic pressure levels maps and cetaceans’ distribution in order to infer the risk of impact and provide management solutions. The methodology, combining simple statistical analyses and a theoretical representation tool was applied to the Bay of Biscay using shipping noise model and fin whale observation from regular surveys for the years 2012 and 2016. Relationships between cetaceans’ distribution and noise levels were investigated and linked to mammals theoretical responses to pressure. A trend analysis between 2012 and 2016 was also proposed to identify the noise hotspots. The results were interpreted in both terms of ecological meaning for fin whale and conservation measures for shipping noise, according to marine policies requirements.

The shipping noise is a major component of the underwater soundscape at low frequency. The increase of the fleet size at world scale for several decades have arisen the potential impacts of noise pollution on marine ecosystems. Modeling the shipping noise levels at large scale became an important task of marine environmental policies. However, because of fluctuating and unknown environmental parameters, the numerical model may present a bias in the estimated levels up to several tens of dB. To tackle this problem, this paper relies on a semi-empirical formulation of the noise level standard deviation, related to environmental mismatch. The model provides monthly noise atlas at world scale, using statistical distribution of shipping. Results are presented using worldwide ship traffic data for the years 2003, 2012, and 2016. It provides a relevant tool to monitor the ambient noise evolution and have been applied for the evaluation of the Marine Strategy Directive Framework.

The management of underwater anthropogenic noise is becoming a significant component of marine policies. Rules to limit noise exposure in a way that marine animals are not adversely affected are expected to be set up in the future. However, modeling or measuring underwater noise levels (orother suitable metrics) can still be subject to a lot of uncertainties due to difficulty in estimatation or measuring key parameters as source pressure levels and waveguide features. On the other hand, the audition threshold values inferred from bioacoustics studies may also lack of statistical robustness and are difficult to generalize. The combination of these two major sources of uncertainties may lead to misestimate the noise exposure risk and may hinder marine space planning efficiency. This work aims at developing a framework for impact studies while considering uncertainties on the acoustic metrics and confidence in the threshold values. It relies on probabilistic description of the acoustics pressure, as proposed...

International audience; In a shallow water environment, wavenumbers can be estimated by computing time and spatial Fourier transforms of horizontal array measurements. The frequency-wavenumber representation allows wide band estimation but a sufficient number of hydrophones are required for accurate wavenumber resolution. This paper presents the application of an autoregressive (AR) model to compute the high resolution wavenumber spectrum. The smallest number of required sensors for the AR model is found using a stabilization diagram. The method is validated on simulated and experimental data. The wavenumbers are accurately estimated over a wide frequency band using fewer sensors than are needed for the spatial Fourier Transform.

International audience; In underwater acoustics, shallow water environments (d

In shallow water, low-frequency acoustic propagation is described by modal theory. In this context, the environment acts as a dispersive waveguide, and the geoacoustic properties of the seabed can be inferred from the modal wavenumbers. When considering horizontal aperture (using a horizontal array or a towed source), wavenumber estimation is a well-known problem, equivalent to spectral analysis. In this paper, wavenumber estimation is revisited using Compressed Sensing (CS). Our method benefits from two strong physical hypotheses. Only a few modes are propagating so that the wavenumber spectrum is sparse. Moreover, if the source is broadband, the wavenumbers can be related from one frequency to the next using a general dispersion relationship. Our method resorts to a state-of-the-art Bayesian algorithm exploiting a Bernoulli-Gaussian model. The latter, well-suited to the sparse representations, makes possible a natural integration of the prior dispersion information through a wise choice of the Bernoulli...