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Due to the addition of new underwater vessels and other natural noise contributors, the underwater environment is becoming congested and noisy. Undersea monitoring sonobuoys receive multiple mixed acoustic signals from different vessels that need to be separated and identified in the presence of underwater noise (UWN). It is extremely challenging to separate highly correlated acoustic signals from a noisy mixture without prior knowledge of mixing process and propagation channel. Also, in many cases, the separated signals from the noisy mixture doesn’t accurately describe the correct signal. This study proposes a novel multi-stage method to separate underwater acoustic source signals from noisy mixture with suppression in noise. The first stage applies multivariate blind source separation (BSS) technique known as non-negative matrix factorization (NMF) that extracts the source signals from the noisy signal mixture. In the second stage, Minimum mean square error (MMSE) estimator is used to reduce noise in separated/reconstructed source signals by minimizing the mean square error (MSE) between reconstructed acoustic signal and original clean signal, enhancing signal reconstruction quality. The results of this study indicate the effectiveness of the proposed method in terms of MSE, signal-to-distortion ratio (SDR) and cepstral distance (CD) and compare it with existing techniques. Based on simulation outcomes our proposed method demonstrates superior separation performance by reducing MSE upto 47% and improving SDR of reconstructed acoustic signals upto 28% compared to existing solutions.

Wind speed and its evolution over time and space are important for many purposes, particularly for climate studies. However, direct measurement at the ocean surface is problematic, and remote prediction using satellite and radar systems rarely offers the desired resolution or accuracy, especially in polar waters. Being able to predict wind speed from underwater acoustic noise is, therefore, a key aspect to improving climate models and monitoring systems. To date, empirical equations using the noise spectrum at a given frequency, fitted to the available data, have been adopted. To leverage on the whole noise spectrum, only recently supervised machine-learning regression has been proposed. This article exploits the concurrent acquisition of underwater noise and anemometer measurements over a period of 16 months, at 10-min steps, to demonstrate the superiority of regression models based on supervised learning over empirical equations. It is also shown that depending on the type of compounding implemented, different tradeoffs are achieved between accuracy and temporal resolution. Considering all samples in the data set, including those in which rainfall and passing ships occurred, and separating by cross-validation the samples used for training from those used for testing, it is shown that a regressor based on the random forest technique, followed by the compounding of the predictions over an interval of 1 h, provides a mean absolute error of 0.62 m/s and a correlation coefficient of 0.96. In addition, the robustness with respect to the parameter setting and the performance obtained in performing prediction in chronological order are evaluated. [ABSTRACT FROM AUTHOR]

To evaluate the performance of underwater acoustic communication systems, it is typically assumed that the noise at the receiver is uncorrelated spatially and temporally. This assumption underestimates the impact of acoustic ocean ambient noise on the performance of communication systems. In this article, the impact of ocean ambient noise on a coherent acoustic communication system is analyzed. The communication performance is assessed in narrowband conditions at a center frequency of ${\text{2.048}\;\text{kHz}}$ using the noise measurements from two different experiments—DalComm1 and the shallow water Canada Basin acoustic propagation experiment (SW CANAPE). DalComm1 focuses on characterizing the acoustic channel over ranges of 1–10 km on the Nova Scotian littoral, while the spatio-temporal variability of noise propagation in shallow and deep water environments was characterized during the CANAPE experiments. The ambient noise coherence and directionality in both environments were also measured. Two distinct noise modeling methodologies are presented to represent realistic synthetic ambient noise with defined directionality. Further, the synthetic noise is validated against measured ambient noise. The impact of ambient noise characteristics on an optimum space-time filter is characterized. A frame structure with an optimum training duration is also defined for the adaptive filter. It is observed that the bit-error rate of the space-time filter depends on optimizing the training and payload duration in the received signal. [ABSTRACT FROM AUTHOR]

The Intensity Vector Autonomous Recorder (IVAR) measures acoustic particle velocity and pressure simultaneously. IVAR was deployed on the seabed during the 2017 Seabed Characterization Experiment (SBCEX) with the primary objective to study sound propagation within underwater waveguides for which the seabed consists of fine-grained, muddy sediments. In this study, a Bayesian framework is applied to underwater noise recorded by IVAR from a cargo ship traversing the central region of the SBCEX2017 area for the purpose of inversion to characterize sediment properties. The vector acoustic data are in the form of a bounded, nondimensional form known as circularity, a quantity that is independent of the ship noise-source spectrum and that can be interpreted as the normalized curl of active intensity. The inversion model space for the seabed consists of a low-compressional speed layer and underlying basement half-space, with each having compressional and shear components. The interpretative model for producing a replica of the data is based on the plane wave reflection coefficient for a layered, elastic seabed in conjunction with the depth-dependent Green’s function that is integrated in the complex wave number plane to obtain pressure and particle velocity fields. The small change in water depth between the location of the ship source and IVAR is addressed using adiabatic mode theory. The inversion results exhibit slow variation over the 20-min observation period, representing approximately 5 km of travel by the ship source. [ABSTRACT FROM AUTHOR]

Underwater acoustic sensor networks (UASNs) have been widely promoted for developing various categories of marine applications, where the sensor nodes cooperate to complete specific tasks. Given the fact that the sensor nodes are unattended while continuously exposed to harsh environments, an associated trust model plays a significant role in node trustworthiness evaluation and defective node detection, such as the case of adverse attacks on the network. However, the existing trust models only evaluate the communication behavior and the energy of the sensor nodes, ignoring the effects of underwater environmental noise on trust reliability. Further, most trust models are designed with arbitraty weighted trust metrics, causing inevitable evaluation errors. To achieve the accurate calculation of node trust, we propose a new anomaly and attack resilient trust model, based on the isolation forest. We refer to this model as ITrust. The proposed ITrust model consists of two phases: trust metrics specifics and defective node detection. In the first phase, the trust dataset is integrated from four types of trust metrics: communication trust, data trust, energy trust, and environment trust. In the second stage, trust is evaluated with the obtained trust dataset using the isolation forest algorithm. Simulation results demonstrate that the proposed ITrust can detect defective nodes effectively, and achieves higher detection accuracy than that of the existing trust models in a noisy environment. [ABSTRACT FROM AUTHOR]

Multi-autonomous underwater vehicles (AUVs) cooperative localization has become a research hotspot in the marine navigation field. In this paper, a filtering algorithm for slave AUV with compass failure is proposed based on ‘two-master-one slave’ cooperative localization model. In this algorithm, the course angle is unknown, and non-Gaussian measurement noise caused by measurement outliers is considered. The cooperative localization model is reconstructed, and a filtering algorithm is derived whose performance will not be affected by the unknown course angle. Moreover, the maximum information potential (MIP) criterion is introduced into a recursive model to deal with the non-Gaussian measurement noise in a complicated underwater environment. Simultaneously, the kernel bandwidth is adaptively adjusted by the innovation matrix and the measurement error covariance matrix. The proposed algorithm can accurately estimate the variation of the unknown course angle without expanding the dimension of state under the condition of non-Gaussian measurement noise. Finally, the proposed algorithm is verified through field experiments. The results show that the proposed algorithm has higher accuracy and robustness than other existing algorithms. [ABSTRACT FROM AUTHOR]

Applications of underwater acoustics include sonar, communication, geophysical imaging, acoustical oceanography, and bioacoustics. Specialists typically work with little interdisciplinary interaction, and the terminology they employ has evolved separately in each discipline, to the point that transdisciplinary misunderstandings are common. Furthermore, increasing societal concern about possible detrimental effects of underwater noise on aquatic animals has led national and international regulators to require monitoring of underwater noise, with a consequent need for interdisciplinary harmonization of terminology. By adopting a common language, we facilitate the effective communication of concepts and information in underwater acoustics, whether for research, technology, or regulation. In the words of William H. Taft, “Don't write so that you can be understood, write so that you can't be misunderstood.” Clear definitions of widely used terms are needed, such as those used for the characterization of sound fields (e.g., “soundscape” and “ambient noise”), sound sources (“source level” and “source waveform”), sound propagation (“transmission loss” and “propagation loss”), and sound reception (“hearing threshold” and “frequency weighting function”). Terms that are used synonymously in one application have different meanings in another (examples include “hearing threshold” versus “detection threshold” and “transmission loss” versus “propagation loss”). Distinct definitions for these and many other acoustic terms are provided in a standard published in April 2017 by the International Organization for Standardization, ISO 18405. This article summarizes ISO 18405 and the process that led to the published definitions, including the reasons for omitting some terms. [ABSTRACT FROM AUTHOR]

Underwater noise analysis allows estimation of parameters of meteorological interest, difficult to monitor with in situ devices, especially in very harsh environments such as polar waters. Rainfall detection is a fundamental step of acoustical meteorology toward quantifying precipitation and, indirectly, wind. To date, this task has been conducted with some success by using a few frequency bins of the noise spectrum and combining their absolute values and slopes into some inequalities. Unfortunately, these algorithms do not perform well when applied to spectra obtained by averaging multiple noise recordings made over the course of an hour. Supervised, machine learning models allow the use of all the frequency bins in the spectrum, exploiting relationships that are difficult for a human observer to identify. Among the different models tested, a binary classifier based on random forest performed well with moderate computational load. Using a dataset consisting of over 18 000 hourly averaged spectra (approximately 25 months of in situ recordings) and comparing the results with measurements from a surface-mounted rain gauge, the proposed system detects precipitations greater than 1 mm/h with 90% probability, keeping the false alarm probability below 0.5%. This system has demonstrated remarkable robustness as performance is achieved without intentionally excluding any spectra corrupted by sounds produced by other sources, such as naval traffic and wind blowing over the sea surface. [ABSTRACT FROM AUTHOR]

The automatic modulation recognition (AMR) enables the receiver to automatically recognize the modulation type of the received signal for achieving correct demodulation. However, the noise and interference in the underwater acoustic channel greatly influence the features extracted from the signals. In this letter, we proposed the optimizing autoencoder (OAE) and the evaluation enhanced K-nearest neighbors (EEKNN) algorithms. The combination of OAE and EEKNN not only improves the feature discrimination but also avoids the misjudgment caused by abnormal samples and realizes accurate and efficient AMR. The experimental results of the data measured in the South China sea show that the proposed method successfully recognizes eight modulation types. The recognition accuracy is up to 99.25%, and the recognition time is only 3.48 ms. [ABSTRACT FROM AUTHOR]

The underwater noise can be caused by the radial electromagnetic vibration of permanent magnet synchronous motor (PMSM) for electric propulsion. The difficulty in decreasing the underwater noise is not only the high-frequency but also low-frequency vibration reduction. This paper proposes a novel random asymmetric carrier pulse width modulation (RACPWM) method for PMSM vibration reduction in the whole frequency range. Instead of the conventional symmetric triangular carrier PWM, the asymmetric carrier PWM (ACPWM) is used to decrease the low-frequency phase current harmonics and the associated low-frequency vibration. Meanwhile, in order to suppress the high-frequency vibration, the RACPWM control based on the amplitude randomization of the sawtooth carrier is further presented to reduce the high-frequency phase current harmonics. Moreover, the RACPWM is equivalent to the random slope ACPWM in view of the output signals. Furthermore, without the need of any additional circuits in the drive, the presented method is simple to implement by software. Simulation and experimental results show that the proposed RACPWM method can effectively reduce both the low-frequency and the high-frequency vibration.

Noise fitting plays a key role in underwater acoustic communications. Traditional approximate models can fit global heavy-tail distribution of the impulsive noise with fixed parameters. These models are unable to cover local distributions with arbitrary lengths. In this paper, we propose a generative-adversarial-network-based underwater noise simulator (GUNS), which constructs a deep-neural-network-based generator and a convolutional-neural-network-based discriminator are constructed to learn the heavy-tail distribution of the impulsive noise. Based on the noise collected in the Wuyuanwan Bay, Xiamen, probability distribution function of the underwater acoustic noise simulated by the proposed GUNS performs lower Kullback-Leibler divergence, Jensen-Shannon divergence and mean square error than that employed traditional approximate models. [ABSTRACT FROM AUTHOR]

Impulsive noise significantly deteriorates the performance of orthogonal frequency-division multiplexing (OFDM)-based underwater acoustic (UWA) communication systems. The pulse blanking (PB) based approach can mitigate the impulsive noise. However, it causes inter-carrier interference (ICI) and signal attenuation to the receiver. In this work, we first show that the ICI introduces pronounced non-Gaussianity to the receiver chain and leads to significant performance degradation. We then propose a non-Gaussianity-aware iterative ICI cancelation scheme to mitigate the adverse impacts of PB. A companding transformation scheme is incorporated into the soft symbol computation to alleviate the non-Gaussianity of the log-likelihood ratios (LLRs) caused by the residual ICI and impulsive noise. Simulation results illustrate that the proposed non-Gaussianity-aware iterative receiver achieves significant performance gains over the conventional non-Gaussianity-agnostic one with even lower computational complexity. [ABSTRACT FROM AUTHOR]

Self-noise of hydrophone is one of the important parameters for critical sonar applications, as it finally decides the lowest detectable signal from a target. To measure the ambient noise of the ocean, the self-noise of the hydrophone should be much less than the sea state zero (SS0) noise. Hence, an experimental setup is required to measure the self-noise generated by the hydrophones. An experimental setup has been designed, developed, and demonstrated. The facility consists of a vibration-isolated and EMI-shielded vacuum chamber which encloses the sample holder assembly and effectively isolates the test hydrophones from external environmental noise sources, such as ground vibrations, electromagnetic interference, and airborne acoustic noises. This enables the measurement of self-noise that is originating purely within the hydrophone. A procedure is developed to remove the noise contribution of the preamplifier including its resistors from the measured output signal of the preamplifier. Uncertainty in measurement using this setup is estimated using the propagation of distribution method through Monte Carlo simulation. This article describes the factors contributing to the self-noise in piezoelectric (PE) transducers, the noise measurement principle, the constructional details of the experimental setup, and the calibration procedure. The technique is demonstrated by measuring the self-noise of a few different types of hydrophones. Thermal noise as low as 0.5 ${\mathrm {nV}} / \sqrt {\mathrm {Hz}} $ with an estimated uncertainty of $0.5~{\mathrm {nV}} / \sqrt {\mathrm {Hz}} $ with a confidence level of 95% is achieved. [ABSTRACT FROM AUTHOR]

Optoelectronic oscillators (OEOs) with their demonstrated low phase noise are popular due to the increasing demand of very clean local oscillator and clock signal sources. A forced technique of self-injection locked and phase-locked loop (SILPLL) reduces phase noise and suppresses side mode observed in long fiber delay of the standard OEO. A frequency synthesizer working at $X$ -band is developed using an electrically coarse-tuned YIG filter cascaded with an optical wavelength fine-tuned dispersive optical transversal filter by tuning the oscillation frequency of the synthesized OEO frequency, as a replacement for fixed-frequency narrowband filter using high- $Q$ aluminum cavities. A close-to-carrier phase noise of −115 dBc/Hz at 1 kHz is reported by the $V_{\pi /2}$ operation of a Mach–Zehnder modulator (MZM) over 8–12 GHz with a frequency tuning step as small as 2.6 kHz. Phase noise introduced by a photodetector is also explored at a very close-to-carrier frequency. It shows 10-dB phase noise degradation at PD reverse bias voltage of 3 V compared with 6 V at close to the $V_{\pi }$ operation of an MZM. A 19-in rack mount frequency synthesizer system is also realized at $X$ -band with a demonstrated long-term (up to 60 min) frequency drift stability of 3 kHz over whole $X$ -band working frequencies. [ABSTRACT FROM AUTHOR]

The autonomous passive-acoustic lander Deep Sound was deployed at five locations during the Office of Naval Research (ONR)-supported Seabed Characterization Experiment, a multi-institutional field effort held at the New England Mud Patch, where the seabed is known to consist of a thick layer of silt and clay overlying a medium and coarse sand. The five deployments of Deep Sound were up to 9 h long, during which time ambient noise data, taken over an acoustic bandwidth of 5 Hz–30 kHz, were collected on four hydrophones arranged in an inverted “T” shape. Local temperature and conductivity were also recorded continuously at each location. A wave number integral model of wind-driven noise in a fluid waveguide over a two-layered elastic seabed was used to calculate the dependence of the vertical noise coherence on the geoacoustic properties in the overlying silt and clay layer, as well as the subbottom sand half-space. The modeled noise coherence was fitted to the data over the band 100 Hz–12 kHz, returning the compressional- and shear-wave speeds and densities of both layers and the thickness of the top layer. [ABSTRACT FROM AUTHOR]

Low visual quality has prevented underwater robotic vision from a wide range of applications. Although several algorithms have been developed, real time and adaptive methods are deficient for real-world tasks. In this paper, we address this difficulty based on generative adversarial networks (GAN), and propose a GAN-based restoration scheme (GAN-RS). In particular, we develop a multibranch discriminator including an adversarial branch and a critic branch for the purpose of simultaneously preserving image content and removing underwater noise. In addition to adversarial learning, a novel dark channel prior loss also promotes the generator to produce realistic vision. More specifically, an underwater index is investigated to describe underwater properties, and a loss function based on the underwater index is designed to train the critic branch for underwater noise suppression. Through extensive comparisons on visual quality and feature restoration, we confirm the superiority of the proposed approach. Consequently, the GAN-RS can adaptively improve underwater visual quality in real time and induce an overall superior restoration performance. Finally, a real-world experiment is conducted on the seabed for grasping marine products, and the results are quite promising. The source code is publicly available 1 [Online]. Available: https://github.com/SeanChenxy/GAN_RS.. [ABSTRACT FROM AUTHOR]

This paper investigates some aspects and features of electrochemical noise measurement instrumentation. A comparison of the resolutions of different analog-to-digital converters demonstrates that converters possessing a resolution of at least 24 bits are preferable due to the significant voltage drift of electrochemical systems. Operational amplifiers having various input types are considered. It is shown that low-noise amplifiers with bipolar input stages are capable of working with low-impedance objects only, such as electrochemical power sources, and that FET input stage amplifiers must be applied when testing the modeling of electrochemical cells having an impedance greater than $50~\Omega $. [ABSTRACT FROM AUTHOR]

GaInAs/InAs composite channels in InP-based pHEMTs enable wideband and/or low-noise performances because of their superior carrier transport properties. To date, the influence of the InAs inset design details on transistor performance has not been parametrized in the literature. We present a systematic study of the effects of the InAs channel inset thickness on transistor characteristics and cutoff frequencies versus temperature, and on the noise performance at 300 K. The epitaxial layer structures considered here incorporate 2 to 5-nm InAs insets in a fixed total composite channel thickness. All layers exhibit excellent electron mobilities (from 40 200 to 54 800 cm2/Vs at 77 K). Thicker InAs insets improve both the current gain cutoff frequency (${f}_{\text {T}}$) and the maximum oscillation frequency (${f}_{\text {MAX}}$). However, they also result in higher gate leakage currents and increased channel impact ionization. 50-nm gate length pHEMTs with a 5-nm InAs inset feature the highest simultaneous ${f}_{\text {T}} / {f}_{\text {MAX}} \ge {390}$ /675 (455/800) GHz at 300 (15) K for a low-noise bias but exhibit the poorest minimum noise figure ${NF}_{\text {MIN}}$. Whereas higher ${f}_{\text {T}}$ (and/or ${f}_{\text {MAX}}$) values have traditionally been associated with improved noise performances, this is no longer the case. [ABSTRACT FROM AUTHOR]

A labeled multi-Bernoulli (LMB) filter is presented to perform multitarget tracking (MTT) for the glint noise. The measurement noise is modeled as a multivariate Student- $t$ process. The variational Bayesian method is applied in the LMB framework with the augmented state. The predictive likelihood is calculated via minimizing the Kullback–Leibler divergence by the variational lower bound. Simulation results show that our approach is effective in MTT with the glint noise. [ABSTRACT FROM AUTHOR]

When designing a low electromagnetic interference (EMI) power electronic converter with high packaging density, its internal near-field coupling to an EMI filter is critical. In this paper, we investigated the near-field coupling between a noise source and a single-phase EMI filter. First, we measured the common-mode (CM) and differential-mode (DM) couplings separately using a four-port network analyzer. The DM coupling when the EMI filter was exposed to a magnetic field was larger than that when it was exposed to an electric field. On the other hand, the CM coupling when the EMI filter was exposed to an electric field was larger than that when it was exposed to a magnetic field. Second, we extracted parasitic coupling elements that determine the coupling magnitude of each mode of coupling. The coupling calculated by the extracted elements agreed with the measurement well. We identified the dominant coupling path between the noise source and the EMI filter. Finally, we studied the required shielding of the EMI filter to reduce the coupling efficiently. Consequently, we found that most of the coupling can be eliminated by shielding the dominant coupling path. [ABSTRACT FROM AUTHOR]

In this paper, we present the results of a comprehensive acoustic monitoring and modeling study of the composite underwater noise footprint of an exploration drilling project in shallow waters (46 m) in the northeastern Chukchi Sea. Measured acoustic source levels of multiple vessels and drilling equipment were used as inputs to theoretical propagation models. The models generated time-dependent wide-area noise fields, accounting for oceanographic and weather conditions and the time-dependent drilling activities and positions of multiple vessels. Modeling in increments of 1 h was performed over the full operations period, from July 7, 2015 to October 16, 2015. Model validation was carried out by comparing simulated results with high-resolution acoustic data acquired at multiple stations in the area. The study shows that noise radiating from up to 19 supporting vessels is usually dominant, but noise from certain drilling-related activities occasionally rises above vessel noise within a radius of 8 km from drill sites, limited to a few hours in durations. Modeled scenarios show that by constraining vessel positions to within a few kilometers of the drilling location, the extent of the 120 dB re 1 μPa noise footprint, as defined for single-well and concurrent double-well drilling operations, is contained within a nominal radius of 20 km. Broadband noise from drilling platforms and support vessels reached wind-generated ambient noise levels at ranges between 60 and 85 km from the drill site. Still, some tones and narrowband sounds may remain above the natural ambient noise at the same frequencies to longer ranges. [ABSTRACT FROM AUTHOR]

We propose a novel stochastic consensus-based secondary voltage and frequency restoration scheme with communication delays and noises for islanded microgrids ($\mu $ Gs). Existing distributed methods commonly design restoration layer with the assumption of ideal communication among distributed generations (DGs). Albeit, the communication channels are exposed to delay and noise, whereas any DG receives delayed and noisy measurements from its neighbors due to peripheral noises and communication delays. Delay and noise have a great impact on the control of $\mu $ G, which terribly reduce the stability and quality of it. To eliminate the adverse effects of delays and noises, we propose a novel consensus protocols that consider effects of the communication noises and delays simultaneously for complete plant dynamics, and study mean square consensus for frequency and voltage restoration of $\mu $ Gs, whereas providing stringent real power sharing. To this end, we derive the mean square consensus restoration proof using rigorous Lyapunov analysis. As a result the suggested method decreases the sensitivity of the system to failures and increases its reliability. Finally, we have done several simulation scenarios in MATLAB/SimPowerSystems Toolbox to verify the proposed strategy performance. [ABSTRACT FROM AUTHOR]

We asked Victoria Vesna for an interview upon investigating her recent collaborative project, Noise Aquarium, through which, together with an interdisciplinary group, she brings awareness to a general audience of underwater noise pollution in relation to the plankton and their plight of coexistence with microplastics in the ocean. The discussion that ensued resonated as to fruitful artistic process, contribution to science, and the organic nature by which many of her most meaningful collaborations evolve to produce art. [ABSTRACT FROM AUTHOR]

We introduce a new algorithm for realizing maximum likelihood (ML) decoding for arbitrary codebooks in discrete channels with or without memory, in which the receiver rank-orders noise sequences from most likely to least likely. Subtracting noise from the received signal in that order, the first instance that results in a member of the codebook is the ML decoding. We name this algorithm GRAND for Guessing Random Additive Noise Decoding. We establish that GRAND is capacity-achieving when used with random codebooks. For rates below capacity, we identify error exponents, and for rates beyond capacity, we identify success exponents. We determine the scheme’s complexity in terms of the number of computations that the receiver performs. For rates beyond capacity, this reveals thresholds for the number of guesses by which, if a member of the codebook is identified, that it is likely to be the transmitted code word. We introduce an approximate ML decoding scheme where the receiver abandons the search after a fixed number of queries, an approach we dub GRANDAB, for GRAND with ABandonment. While not an ML decoder, we establish that the algorithm GRANDAB is also capacity-achieving for an appropriate choice of abandonment threshold, and characterize its complexity, error, and success exponents. Worked examples are presented for Markovian noise that indicate these decoding schemes substantially outperform the brute force decoding approach. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) systems have become popular as one of the renewable energy sources in recent years. With increasing number of PV systems, potential electromagnetic interference (EMI) issues from the PV systems cannot be ignored. In order to evaluate the EMI potential of a PV system, an in-circuit measurement method to extract its equivalent common-mode and differential-mode noise source models is described and validated. These noise source models serve as black boxes for further EMI analyses. [ABSTRACT FROM AUTHOR]

This paper proposed a novel hybrid random pulsewidth modulation (HRPWM) technique based on the modified space vector PWM for three-phase voltage source inverters to eliminate the PWM acoustic noise. Due to PWM technique and switching losses considerations, ear-piercing high-frequency noise from motor is common. The proposed HRPWM technique is able to remove the high-frequency unpleasant acoustic noise more effectively than the conventional RPWM with lower switching losses and shorter random frequency range. In addition, the PWM harmonics in phase voltage and phase current are reduced significantly. The HRPWM method is simple to implement and does not employ additional circuits in drive system. Finally, the effectiveness of the proposed approach has been confirmed by detailed experimental results. [ABSTRACT FROM AUTHOR]

Diffusion-based molecular communication (DMC) is one of the most promising approaches for realizing nano-scale communications for healthcare applications. The DMC systems in in-vivo environments may encounter biological entities that release molecules identical to the molecules used for signaling as part of their functionality. Such entities in the environment act as external noise sources from the DMC system’s perspective. In this paper, the release of molecules by external bio-inspired noise sources is particularly modeled as a compound Poisson process. The impact of compound Poisson noise sources (CPNSs) on the performance of a point-to-point DMC system is investigated. To this end, the noise from the CPNS observed at the receiver is characterized. Considering a simple on-off keying modulation and formulating symbol-by-symbol maximum likelihood (ML) detector, the performance of the DMC system in the presence of the CPNS is analyzed. For the special case of CPNS in a high-rate regime, the noise received from the CPNS is approximated as a Poisson process whose rate is normally distributed. In this case, it is proved that a simple single-threshold detector is an optimal ML detector. Our results reveal that in general, adopting the conventional simple homogeneous Poisson noise model may lead to overly optimistic performance predictions, if a CPNS is present. [ABSTRACT FROM AUTHOR]

Porous materials are frequently used for noise reduction in acoustical applications with air. These types of materials lose their absorbing capacity when saturated by liquids. To reduce the underwater noise radiated by ships, metallic foams are specifically designed for acoustical dissipation when saturated by diesel, to use them as a covering in the interior of fuel tanks. The aim is to attract and dissipate noise in the fuel tanks by means of the diesel-foam viscous coupling. For this aim, analytical solutions of the reflection, absorption, and transmission coefficients have been developed. The interior covering of the tank wall with the metallic foam could produce reductions of transmitted sound to the ocean over 10 dB if the metallic foam is properly designed. [ABSTRACT FROM AUTHOR]

Impulsive noise is one key factor that limits the performance of underwater acoustic (UA) communications. In this paper, two pilot-subcarrier based algorithms are proposed to improve the performance of channel estimation and impulsive noise mitigation for UA orthogonal frequency-division multiplexing (OFDM) systems. The first algorithm jointly estimates the channel and the impulsive noise based on the least-squares principle. The second algorithm is developed with the aim to reduce the computational complexity, where the expectation-maximization principle is applied to estimate the channel and the impulsive noise iteratively. We compare the proposed algorithms by simulations and apply them to process the data collected during an experiment conducted in December 2015 in the estuary of the Swan River, Western Australia. The results show that both proposed algorithms have better performance than existing methods in mitigating impulsive noise in UA OFDM systems. [ABSTRACT FROM PUBLISHER]

In this paper, a technique is presented for frequency-smoothing the sample covariance matrix observed at the output of a set of elements or beams so as to obtain a frequency-smoothed estimate of the broadband noise covariance matrix due to underwater noise. The smoothing technique is based on a linear model that is derived through analysis of the delay-domain cross covariance of the ambient noise observed by a pair of beams or omnidirectional hydrophones. A simple and robust least squares fitting algorithm allows for extraction of a frequency-smoothed broadband noise covariance estimate even in the presence of narrowband energy. Simulated passive sonar examples demonstrate the validity and utility of the estimate. Possible applications include adaptive beamforming and measuring the vertical/horizontal directionality of diffuse broadband ambient noise sources such as wind and rain. [ABSTRACT FROM AUTHOR]

The contribution of shipping noise to the background noise in the seas can be estimated by shipping noise maps. Noise maps can be made by applying appropriate modeling tools for underwater sound propagation and ship source levels to information on the acoustic environment and on the ship traffic in the area of the map. The development of reliable source level models requires the availability of a variety of radiated noise data of ships. Therefore, full-scale radiated noise measurements were performed near a shipping lane in coastal waters out of the Port of Rotterdam. The results of the noise measurements are combined with information about the measured ships and their positions, derived from registered AIS data, and with propagation conditions to determine source levels. Criteria have been developed to select the data from which a reliable source level estimation can be obtained from individual ship passages at the busy shipping lanes. Source levels of different types of ships are compared. [ABSTRACT FROM AUTHOR]

There is increasing concern within the scientific community about the underwater noise due to anthropogenic activity and its impact on marine life, with negative consequences on biodiversity and sea resources. In that context, the European Marine Strategy Framework Directive stated in 2008 that the anthropogenic noise due to shipping was to be mitigated. To address this issue, the European Union (EU) project “Achieve QUieter Oceans by shipping noise footprint reduction” (AQUO) (www.aquo.eu) started in October 2012 with a duration of four years. The project brought together experts from shipbuilding, underwater acoustics, and bioacoustics, with a multidisciplinary approach. In this paper, after giving a brief overview of the project structure, the methodology proposed by the AQUO project to set guidelines for controlling the underwater noise from commercial shipping is presented in more detail. Such a methodology is aimed at identifying the most promising strategies for the mitigation of the impact of shipping noise on marine fauna. Different technical as well as operational solutions are evaluated by taking into account the impact on marine life, the feasibility in terms of ship design, and the cost effectiveness, also considering fuel efficiency. While technical solutions are usually more effective at the design stage both in terms of costs and performance, operational solutions can potentially be adopted without any modification to the existing fleet. Furthermore, operational prescriptions can be set by national/local authorities who cannot directly intervene on ship configurations. The different solutions have been evaluated by means of numerical modeling carried out by using a Noise Footprint Assessment Model derived from the Quonops tool. [ABSTRACT FROM AUTHOR]

Awareness of underwater noise from shipping has grown significantly within the marine community over the past decade. Concerns have been raised about the levels of anthropogenic noise in the world's oceans, as well as in harbors and areas with sensitive or protected marine life. Regulatory bodies are listening, and are considering what actions are available to reduce noise. Measurements of vessel noise in various situations have been performed to better quantify the problem, and efforts have been made by some to correlate noise levels with simplified vessel parameters. Such efforts provide insights into what levels of noise are possible and how they are related to ship operation. However, to reduce underwater noise, a deeper understanding of specific vessel design and factors that lead to noise are required. While generalities of primary noise sources can be applied to different classes of vessels, design details of specific vessels must be obtained and analyzed to implement noise reductions. Armed with knowledge of vessel details, noise control strategies can be optimized using various computer-aided tools. This must be done on a case-by-case basis for different vessel designs, and is most efficient and effective for new builds. Costs for such efforts must also be considered if vessel noise is to be made inherently quieter worldwide. [ABSTRACT FROM AUTHOR]

Machinery vibration is a significant source of noise from marine vessels. Consequently, problematic machinery is often decoupled from the hull using resilient mounts. When radiated noise is a priority, two-stage mounting arrangements can be used which provide superior performance. This improvement, however, comes at a much higher weight and cost. A commonly overlooked issue with isolation systems is that the individual mounts suffer from internal resonances which reduce their effectiveness. This paper broadly evaluates the influence of these on the underwater noise levels from a typical ship diesel. The effect of nonrigid structural components, that is, the supported machine, the machine foundation, and the intermediate mass in two-stage mounting arrangements, is also discussed. The structureborne and airborne transmission paths are resolved individually using approximate analytical methods, and the source levels are estimated from empirical relationships for typical marine diesels. It is shown that, by mitigating the internal resonances of the mounts, a two-stage mounting arrangement may be unnecessary because of the contribution to the underwater noise by airborne transmission. [ABSTRACT FROM AUTHOR]

A growing attention has been recently devoted to the impact of the underwater noise field generated by shipping activities on the marine fauna. A key aspect for the quantification of such impact is a proper model of the source levels radiated from the vessels. At a first level of approximation, simplified formulations based on a small number of macroparameters describing the ship characteristics are needed to quantify the emission and, accordingly, assess the noise impact and evaluate strategies for its control. In fact, a few models of this kind are available in the literature, mainly based on measurements and databases developed for military purposes. Most of these models have been tuned on old ships: this poses the question whether they are still applicable to modern commercial vessels. In this work, spectra of a series of measurements of underwater noise emitted by commercial vessels measured in the framework of two EU FP7 projects (SILENV: www.silenv.eu and AQUO: www.aquo.eu) are analyzed and compared with the results obtained applying the available literature models. The analysis is carried out for noise emitted both at design and off-design conditions. In such conditions, the models are also compared with a proposed spectral parametrization. Focusing on the off-design conditions, a detailed narrow band analysis of a complete set of noise spectra is presented for a ship equipped with a controllable pitch propeller (CPP). The spectral peculiarities of such a propulsion plant, when operated at constant revolutions per minute (RPM) are highlighted. Results of the suggested parametrization applied to the same ship are presented together with the data of other CPP ships and a critical analysis is carried out discussing the limits of the existing predictive models. [ABSTRACT FROM AUTHOR]

Noise reduction capacity in sensor array signal processing is derived under the assumption of white noise, where the noise reduction is defined as the difference between the input noise power and the output noise power in this paper. However, the underwater noise mainly includes white noise and correlated noise. In this situation, the noise reduction capacity may be deteriorated considerably in actual underwater environment. To tackle this problem, a new noise reduction method, which is named imaginary delay-and-sum beamforming method, is proposed. First, the noise signals received by a sensor array are decomposed into symmetrical and asymmetrical components. Theoretically, the symmetrical component can only affect the real parts of the noise covariance matrix. Then, the real parts of the data covariance matrix are eliminated to reduce the symmetrical noise, and the beamforming is completed by using only imaginary parts. The output signal-to-noise ratio is improved and the root mean square error of the direction-of-arrival estimation is decreased. Theoretical analyses and experimental results show that the proposed method can be easily implemented to improve the noise reduction capacity in sensor array signal processing. [ABSTRACT FROM PUBLISHER]

In this paper, the problem of minimizing the noise generated by the propeller and the control surfaces of a manned submarine is addressed. Cavitation attached to propeller blades and hydrofoils as well as vortex cavitation occurring at a distance from propeller blades and hydrofoils which is generated by turbulent boundary layers is considered. The main goal is to compute trajectories for different tactically relevant maneuvers that minimize the noise generated by its associated prevalent source. To this end, we consider a constrained, nonlinear, optimal control problem which has a system of 12 nonlinear differential equations as the underlaying state law and a Bolza-type cost function. The control variables are propeller revolutions, deflections of control surfaces, and the rate at which they change. After a suitable change of variables, the existence of a solution for the control problem is proved by using Filippov's theory. The problem is solved numerically with a descent method. A couple of numerical simulations complete our study. [ABSTRACT FROM PUBLISHER]

A new algorithmic framework for sparse channel identification is proposed. Although the focus of this paper is on sparse underwater acoustic channels, this framework can be applied in any field where sequential noisy signal samples are obtained from a linear time-varying system. A suit of new algorithms is derived by minimizing a differentiable cost function that utilizes the underlying Riemannian structure of the channel as well as the L0-norm of the complex-valued channel taps. The sparseness effect of the proposed algorithms is successfully demonstrated by estimating a mobile shallow-water acoustic channel. The clear superiority of the new algorithms over state-of-the-art sparse adaptive algorithms is shown. Moreover, the proposed algorithms are employed by a channel-estimate-based decision-feedback equalizer (CEB DFE). These CEB DFE structures are compared with a direct-adaptation DFE (DA DFE), which is based on sparse and nonsparse adaptation. Our results confirm the improved error-rate performance of the new CEB DFEs when the channel is sparse. [ABSTRACT FROM PUBLISHER]