2,953 research outputs found

    Single-channel blind source separation of underwater acoustic signals using improved NMF and FastICA

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    When automatic monitoring buoys receive mixed acoustic signals from multiple underwater acoustic targets, the statistical blind source separation (BSS) task is used to separate the signals and identify vessel features, which is overly complex and needs improvement, especially noting that noise cancellation and stealth technologies are advancing rapidly. To fill this gap in capability, an improved non-negative matrix factorization (NMF) based BSS algorithm is built on a FastICA machine learning backbone. With this tool, the spatial and spectral correlation of underwater acoustic signals is introduced into the NMF algorithm improved by to resolve the non-convex and feature correlation problems commonly encountered by contemporary NMF algorithms. Moreover, the improved modulation feature adaptability of the NMF increases the local expressivity and independence of the decomposed base matrix, which is proven to meet the requirements of FastICA and used to improve the BSS effect of the FastICA. Simulated and empirical results show that compared with state-of-the-art FastICA and NMF based BSS algorithms, our novel approach obtains better signal-to-noise reduction and separation accuracy while maintaining superior target signal recognition features

    Source localization using acoustic vector sensors: a music approach

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    Traditionally, a large array of microphones is used to localize multiple far field sources in acoustics. We present a sound source localization technique that requires far less channels and measurement locations (affecting data channels, setup times and cabling issues). This is achieved by using an acoustic vector sensor (AVS) in air that consists of four collocated sensors: three orthogonally placed acoustic particle velocity sensors and an omnidirectional sound pressure transducer. Experimental evidence is presented demonstrating that a single 4 channel AVS based approach accurately localizes two uncorrelated sources. The method is extended to multiple AVS, increasing the number of sources that can be identified. Theory and measurement results are presented. Attention is paid to the theoretical possibilities and limitations of this approach, as well as the signal processing techniques based on the MUSIC method

    Ecosystem Monitoring and Port Surveillance Systems

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    International audienceIn this project, we should build up a novel system able to perform a sustainable and long term monitoring coastal marine ecosystems and enhance port surveillance capability. The outcomes will be based on the analysis, classification and the fusion of a variety of heterogeneous data collected using different sensors (hydrophones, sonars, various camera types, etc). This manuscript introduces the identified approaches and the system structure. In addition, it focuses on developed techniques and concepts to deal with several problems related to our project. The new system will address the shortcomings of traditional approaches based on measuring environmental parameters which are expensive and fail to provide adequate large-scale monitoring. More efficient monitoring will also enable improved analysis of climate change, and provide knowledge informing the civil authority's economic relationship with its coastal marine ecosystems

    Wireless Sensor Networks for Ecosystem Monitoring & Port Surveillance

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    International audienceProviding a wide variety of the most up - to - date innovations in sensor technology and sensor networks, our current project should achieve two major goals. The first goal covers various issues related to the public maritime transport safety and security, such as the coastal and port surveillance systems. While the second one w ill improve the capacity of public authorities to develop and implement smart environment policies by monitoring the shallow coastal water ecosystems. At this stage of our project, a surveillance platform has been already installed near the "MolĂšne Island" which is a small but the largest island of an archipelago of many islands located off the West coast of Brittany in North Western France. Our final objective is to add various sensors as well as to design, develop and implement new algorithms to extend th e capacity of the existing platform and reach the goals of our project. Finally, this manuscript introduces the identified approaches as well as t he second phase of the project which consists in analyzing living underwater micro - organisms (the population o f Marine Micro - Organisms, i.e. MMOs such as Phytoplankton and Zooplankton micro - zooplankton, but also heterotrophic bacterioplankton) in order to predict the health conditions of the macro - environment s . In addition, this communication discusses developed t echniques and concepts to deal with several practical problems related to our project. Some results are given and the whole system architecture is briefly described. This manuscript will also addresses the national benefit of such projects in the case of t hree different countries (Australia, France and KS

    Challenges and methodologies in Passive Ocean Acoustic Tomography: An approach based on ICA

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    International audienceThe main idea of this manuscript consists on applying signal processing methods along with statistical approaches to achieve the characteriza- tion of a complex and hostile environment such as the oceanic underwater environment. In order to study, characterize (i.e. the measurement of the pressure, the salinity, the temperature, etc.) and extract the topographical features (depth, etc), Ocean acoustic tomography methods are widely used. For many reasons, Passive ocean Acoustic Tomography (PAT) configuration becomes more attractive than the classic active one. However the new passive configuration is more challenging. In our project, some of the facing problems have been addressed. In this manuscript, major problems are described and a new separation scheme based on modified ICA algorithms is proposed. Finally, our experiment results corroborate the effectiveness of our proposed approach. KEY WORD: Underwater acoustic applications, passive acoustic tomography, second order statistics in frequency domain, multipath channel, sparseness or non-stationary signals

    Source Separation of Unknown Numbers of Single-Channel Underwater Acoustic Signals Based on Autoencoders

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    The separation of single-channel underwater acoustic signals is a challenging problem with practical significance. Few existing studies focus on the source separation problem with unknown numbers of signals, and how to evaluate the performances of the systems is not yet clear. We propose a solution with a fixed number of output channels to address these two problems, enabling it to avoid the dimensional disaster caused by the permutation problem induced by the alignment of outputs to targets. Specifically, we propose a two-step algorithm based on autoencoders and a new performance evaluation method for situations with mute channels. Experiments conducted on simulated mixtures of radiated ship noise show that the proposed solution can achieve similar separation performance to that attained with a known number of signals. The proposed algorithm achieved competitive performance as two algorithms developed for known numbers of signals, which is highly explainable and extensible and get the state of the art under this framework.Comment: 14 pages, 4 figures, 3 tables. For codes, see https://github.com/QinggangSUN/unknown_number_source_separatio

    TS-MUWSN: Time synchronization for mobile underwater sensor networks

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    Time synchronization is an important, yet challenging, problem in underwater sensor networks (UWSNs). This challenge can be attributed to: 1) messaging timestamping; 2) node mobility; and 3) Doppler scale effect. To mitigate these problems, we present an acoustic-based time-synchronization algorithm for UWSN, where we compare several message time-stamping algorithms in addition to different Doppler scale estimators. A synchronization system is based on a bidirectional message exchange between a reference node and a slave one, which has to be synchronized. Therefore, we take as reference the DA-Sync-like protocol (Liu et al., 2014), which takes into account node's movement by using first-order kinematic equations, which refine Doppler scale factor estimation accuracy, and result in better synchronization performance. In our study, we propose to modify both time-stamping and Doppler scale estimation procedures. Besides simulation, we also perform real tests in controlled underwater communication in a water test tank and a shallow-water test in the Mediterranean Sea.Peer ReviewedPostprint (author's final draft
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