Cross Recurrence Plot Analysis Based Method For TDOA Estimation Of Underwater Acoustic Signals

International audience—In this paper, we propose to use cross recurrence plot analysis (CRPA) to estimate the time-difference of arrival (TDOA) of underwater acoustic signals arriving on an array of hydrophones. Instead of considering the signal as a whole to estimate the TDOA, like classical methods do, we first detected the series of samples that look alike on each pair of hydrophones of the array by using cross-recurrence plot analysis. The TDOA is then estimated by relying only on these common sample series. The TDOA estimator is based on quantification measures specifically designed for CRPA. The proposed method is successfully validated on real data containing frequency-modulated sounds from beluga whales

Time-Difference-of-Arrival Estimation Based on Cross Recurrence Plots, with Application to Underwater Acoustic Signals

International audienceThe estimation of the time difference of arrival (TDOA) consists of the determination of the travel-time of a wavefront between two spatially separated receivers , and it is the first step of processing systems dedicated to the identification, localization and tracking of radiating sources. This article presents a TDOA estima-tor based on cross recurrence plots and on recurrence quantification analysis. Six recurrence quantification analyses measures are considered for this purpose, including two new ones that we propose in this article. Simulated signals are used to study the influence of the parameters of the cross recurrence plot, such as the embedding dimension, the similarity function, and the recurrence threshold, on the reliability and effectiveness of the estimator. Finally, the proposed method is validated on real underwater acoustic data, for which the cross recurrence plot estimates correctly 77.6% of the TDOAs, whereas the classical cross-correlation estimates correctly only 70.2% of the TDOAs

Time-delay estimation based on Cross Recurrence Plot and Joint Recurrence Plot for passive underwater acoustic source localization

International audiencePassive acoustic localization of underwater sources, like cetaceans, is generally based on a two steps approach. First step consists in a time-delay estimation (TDE), which aims at measuring the relative time difference of arrival (TDOA) of the signal on spatially separated sensors. Second step consists in determining the position of the source from a set of estimated TDOA related to the array geometry, by using a spatial inversion algorithm. In this presentation we only focus on the first step. The most popular method for time-delay estimation in underwater acoustic is the cross-correlation. However, this method has some weaknesses when the signal of interest is mixed in high-level background noise and propagate in reverberant and dispersive environment that warp the waveform of the signals received at different sensors. In such conditions, the cross-correlation gives poor and unreliable estimates of the time-delay, particularly if a low percentage of samples look alike on the different sensors.In this presentation, we propose to use Cross Recurrence Plot (CRP) and Joint Recurrence Plot (JRP) to estimate the time-delay. First, we identify samples that are recurrent on the different sensors, by calculating the CRP and the JRP between pairs of sensors. Then, we use recurrence quantification analysis (RQA) to estimate the time-delay. Several RQA metrics such as the longest diagonal line Lmax , the longest curved trace, the diagonal-wise tau-recurrence rate, the recurrence rate and the joint probability of recurrence are considered for this purpose. The most reliable RQA metric for TDE is determined through performance analysis tests involving simulated signals with known time-delay. The influence of the embedding dimension m, of the delay tau and of the recurrence threshold on the performances of the TDE are also discussed. Finally, the proposed method is validated on real data recorded at sea by an hydrophone array and containing cetacean and fish vocalizations

Détection, localisation, caractérisation de transitoires acoustiques sous-marins

The underwater environment is insonified by a wide variety of acoustic sourcesthat can be monitored by autonomous passive acoustic recorders. A large number of the recordedsounds are transient signals (short-finite duration signals), among which the pulse signals that westudy in this thesis. Pulse signals have specific properties, such as a very short duration (<1ms), fewoscillations, a high directivity, which make them difficult to study by classical signal processing tools(Fourier transform, autocorrelation).In the first part of this study, we develop a method to detect sound sources emitting rhythmic pulsetrains (dolphins, sperm whales, beluga whales). This detector uses only the time of arrival of pulses atthe hydrophone to perform a rhythm analysis based on a complex autocorrelation and a time-rhythmrepresentation. This allows : i) to detect rhythmic pulse trains, ii) to know the beginning and endingtimes of pulse trains, iii) to know the value of the rhythm.In the second part of this thesis, we study the potential of a method called Recurrence Plot Analysis tocharacterize waveforms of pulse signals. After a general presentation of this method we develop threesignal processing architectures based on it, to perform the following tasks : i) transient detection, ii)transient characterization and pattern recognition, iii) estimation of time difference of arrival of thetransient on two hydrophones.All the methods developped in this thesis are validated on simulated and real data recorded at sea.Le milieu marin est insonifié par une grand variété de sources acoustiques, qui peuventêtre monitorées par des enregistreurs acoustiques passifs autonomes. Parmi les sons enregistrés, ontrouve un grand nombre de signaux transitoires (signaux éphémères de durée courte), auxquelsappartiennent notamment les signaux impulsionnels que nous étudions dans cette thèse. Les signauximpulsionnels ont des propriétés spécifiques, telles que leur durée très courte (<1ms), leur faiblenombre d’oscillations, leur forte directivité, qui les rendent difficiles à étudier avec les outils detraitement du signal traditionnels (transformée de Fourier, autocorrélation, etc.).Dans un premier temps, nous nous intéressons à la détection des sources qui émettent des sériesd’impulsions rythmées (dauphins, cachalots, bélugas). Cette détection, s’appuie uniquement surles temps d’arrivée des impulsions reçues, pour effectuer une analyse du rythme au moyen d’uneautocorrélation complexe, et construire une représentation temps-rythme, permettant : i) de détecterles rythmes, ii) de connaître les temps de début et fin des émissions rythmées, iii) de connaître lavaleur du rythme et son évolution.Dans un second temps, nous étudions le potentiel d’une technique appelée analyse par récurrence desphases, pour caractériser les formes d’onde des impulsions. Après avoir présenté le cadre général decette méthode d’analyse, nous l’utilisons dans trois chaînes de traitement répondant à chacune destâches suivantes : i) détection des transitoires, ii) caractérisation et reconnaissance des transitoires,iii) estimation des différences des temps d’arrivée des transitoires sur deux capteurs.Toutes les méthodes développées dans cette étude ont été testées et validées sur des données simuléeset sur des données réelles acquises en me

Bimodal sound source tracking applied to road traffic monitoring

The constant increase of road traffic requires closer and closer road network monitoring. The awareness of traffic characteristics in real time as well as its historical trends, facilitates decision-making for flow regulation, triggering relief operations, ensuring the motorists’ safety and contribute to optimize transport infrastructures. Today, the heterogeneity of the available data makes their processing complex and expensive (multiple sensors with different technologies, placed in different locations, with their own data format, unsynchronized, etc.). This leads metrologists to develop “smarter” monitoring devices, i.e. capable of providing all the necessary data synchronized from a single measurement point, with no impact on the flow road itself and ideally without complex installation. This work contributes to achieve such an objective through the development of a passive, compact, non-intrusive, acoustic-based system composed of a microphone array with a few number of elements placed on the roadside. The proposed signal processing techniques enable vehicle detection, the estimation of their speed as well as the estimation of their wheelbase length as they pass by. Sound sources emitted by tyre/road interactions are localized using generalized cross-correlation functions between sensor pairs. These successive correlation measurements are filtered using a sequential Monte Carlo method (particle filter) enabling, on one hand, the simultaneous tracking of multiple vehicles (that follow or pass each other) and on the other hand, a discrimination between useful sound sources and interfering noises. This document focuses on two-axle road vehicles only. The two tyre/road interactions (front and rear) observed by a microphone array on the roadside are modeled as two stochastic, zero-mean and uncorrelated processes, spatially disjoint by the wheelbase length. This bimodal sound source model defines a specific particle filter, called bimodal particle filter, which is presented here. Compared to the classical (unimodal) particle filter, a better robustness for speed estimation is achieved especially in cases of harsh observation. Moreover the proposed algorithm enables the wheelbase length estimation through purely passive acoustic measurement. An innovative microphone array design methodology, based on a mathematical expression of the observation and the tracking methodology itself is also presented. The developed algorithms are validated and assessed through in-situ measurements. Estimates provided by the acoustical signal processing are compared with standard radar measurements and confronted to video monitoring images. Although presented in a purely road-related applied context, we feel that the developed methodologies can be, at least partly, applied to rail, aerial, underwater or industrial metrology

Performance analysis of frequency shift estimation techniques in Brillouin distributed fiber sensors

The performance of post-processing techniques carried out on the Brillouin gain spectrum to estimate the Brillouin frequency shift (BFS) in standard Brillouin distributed sensors is evaluated. Curve fitting methods with standard functions such as polynomial and Lorentzian, as well as correlation techniques such as Lorentzian Cross-correlation and Cross Reference Plot Analysis (CRPA), are considered for the analysis. The fitting procedures and key parameters for each technique are optimized, and the performance in terms of BFS uncertainty, BFS offset error and processing time is compared by numerical simulations and through controlled experiments. Such a quantitative comparison is performed in varying conditions including signal-to-noise ratio (SNR), frequency measurement step, and BGS truncation. It is demonstrated that the Lorentzian cross-correlation technique results in the largest BFS offset error due to truncation, while exhibiting the smallest BFS uncertainty and the shortest processing time. A novel approach is proposed to compensate such a BFS offset error, which enables the Lorentzian cross-correlation technique to completely outperform other fitting methods

Exploring Animal Behavior Through Sound: Volume 1

This open-access book empowers its readers to explore the acoustic world of animals. By listening to the sounds of nature, we can study animal behavior, distribution, and demographics; their habitat characteristics and needs; and the effects of noise. Sound recording is an efficient and affordable tool, independent of daylight and weather; and recorders may be left in place for many months at a time, continuously collecting data on animals and their environment. This book builds the skills and knowledge necessary to collect and interpret acoustic data from terrestrial and marine environments. Beginning with a history of sound recording, the chapters provide an overview of off-the-shelf recording equipment and analysis tools (including automated signal detectors and statistical methods); audiometric methods; acoustic terminology, quantities, and units; sound propagation in air and under water; soundscapes of terrestrial and marine habitats; animal acoustic and vibrational communication; echolocation; and the effects of noise. This book will be useful to students and researchers of animal ecology who wish to add acoustics to their toolbox, as well as to environmental managers in industry and government

Exploring Animal Behavior Through Sound: Volume 1

This open-access book empowers its readers to explore the acoustic world of animals. By listening to the sounds of nature, we can study animal behavior, distribution, and demographics; their habitat characteristics and needs; and the effects of noise. Sound recording is an efficient and affordable tool, independent of daylight and weather; and recorders may be left in place for many months at a time, continuously collecting data on animals and their environment. This book builds the skills and knowledge necessary to collect and interpret acoustic data from terrestrial and marine environments. Beginning with a history of sound recording, the chapters provide an overview of off-the-shelf recording equipment and analysis tools (including automated signal detectors and statistical methods); audiometric methods; acoustic terminology, quantities, and units; sound propagation in air and under water; soundscapes of terrestrial and marine habitats; animal acoustic and vibrational communication; echolocation; and the effects of noise. This book will be useful to students and researchers of animal ecology who wish to add acoustics to their toolbox, as well as to environmental managers in industry and government

Acoustic source localisation and tracking using microphone arrays

This thesis considers the domain of acoustic source localisation and tracking in an indoor environment. Acoustic tracking has applications in security, human-computer interaction, and the diarisation of meetings. Source localisation and tracking is typically a computationally expensive task, making it hard to process on-line, especially as the number of speakers to track increases. Much of the literature considers single-source localisation, however a practical system must be able to cope with multiple speakers, possibly active simultaneously, without knowing beforehand how many speakers are present. Techniques are explored for reducing the computational requirements of an acoustic localisation system. Techniques to localise and track multiple active sources are also explored, and developed to be more computationally efficient than the current state of the art algorithms, whilst being able to track more speakers. The first contribution is the modification of a recent single-speaker source localisation technique, which improves the localisation speed. This is achieved by formalising the implicit assumption by the modified algorithm that speaker height is uniformly distributed on the vertical axis. Estimating height information effectively reduces the search space where speakers have previously been detected, but who may have moved over the horizontal-plane, and are unlikely to have significantly changed height. This is developed to allow multiple non-simultaneously active sources to be located. This is applicable when the system is given information from a secondary source such as a set of cameras allowing the efficient identification of active speakers rather than just the locations of people in the environment. The next contribution of the thesis is the application of a particle swarm technique to significantly further decrease the computational cost of localising a single source in an indoor environment, compared the state of the art. Several variants of the particle swarm technique are explored, including novel variants designed specifically for localising acoustic sources. Each method is characterised in terms of its computational complexity as well as the average localisation error. The techniques’ responses to acoustic noise are also considered, and they are found to be robust. A further contribution is made by using multi-optima swarm techniques to localise multiple simultaneously active sources. This makes use of techniques which extend the single-source particle swarm techniques to finding multiple optima of the acoustic objective function. Several techniques are investigated and their performance in terms of localisation accuracy and computational complexity is characterised. Consideration is also given to how these metrics change when an increasing number of active speakers are to be localised. Finally, the application of the multi-optima localisation methods as an input to a multi-target tracking system is presented. Tracking multiple speakers is a more complex task than tracking single acoustic source, as observations of audio activity must be associated in some way with distinct speakers. The tracker used is known to be a relatively efficient technique, and the nature of the multi-optima output format is modified to allow the application of this technique to the task of speaker tracking