Pub Date : 2008-10-01DOI: 10.1109/PASSIVE.2008.4786980
J. Barhen, T. Humble, M. Traweek
The concept of ldquocorner turningrdquo has been, for many decades, at the heart of array beamforming via Fourier transforms. As widely reported in the open literature (both for sonars and radars), corner turning operations in the computational sequence Lttemporal Fourier transforms rarr data cube corner turning rarr spatial Fourier transformsGt, constitute a major obstacle to achieve high-performance and lower power dissipation (by reducing the number memory accesses). To date, leading industry providers still include explicit corner turning stages in their computational flow architectures for multidimensional array processing. The emergence of ultra-low power multicore processors opens unprecedented opportunities for implementing sophisticated signal processing algorithms faster and within a much lower energy budget. In that context, the primary innovation reported in this paper addresses the development of a computational scheme that avoids altogether the corner turning stage. We discuss its implementation on an IBM Cell multicore processor (Sony PS3) and provide preliminary timing results.
{"title":"FFT-based sonar array beamforming without corner turning","authors":"J. Barhen, T. Humble, M. Traweek","doi":"10.1109/PASSIVE.2008.4786980","DOIUrl":"https://doi.org/10.1109/PASSIVE.2008.4786980","url":null,"abstract":"The concept of ldquocorner turningrdquo has been, for many decades, at the heart of array beamforming via Fourier transforms. As widely reported in the open literature (both for sonars and radars), corner turning operations in the computational sequence Lttemporal Fourier transforms rarr data cube corner turning rarr spatial Fourier transformsGt, constitute a major obstacle to achieve high-performance and lower power dissipation (by reducing the number memory accesses). To date, leading industry providers still include explicit corner turning stages in their computational flow architectures for multidimensional array processing. The emergence of ultra-low power multicore processors opens unprecedented opportunities for implementing sophisticated signal processing algorithms faster and within a much lower energy budget. In that context, the primary innovation reported in this paper addresses the development of a computational scheme that avoids altogether the corner turning stage. We discuss its implementation on an IBM Cell multicore processor (Sony PS3) and provide preliminary timing results.","PeriodicalId":153349,"journal":{"name":"2008 New Trends for Environmental Monitoring Using Passive Systems","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115363866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-10-01DOI: 10.1109/PASSIVE.2008.4787002
Q. Li, S. Reboul, S. Boutoille, J. Choquel, M. Benjelloun, A. Gardel
In this work we investigate the potential for sensing beach soil moisture with the L band GPS bistatic radar concept. Characterisation of sediment surface (properties like humidity) is indeed important to better understand morphodynamic activity of intertidal part of beaches. In our approach we compare the direct GPS Signal to Noise Ratio with the reflected one in order to measure the soil moisture. We use a bit grabber to digitize and store the GPS L1 carrier (1.5 Ghz) samples. In this context the signal processing is off-line. In this work we proposed a model of the received signal after demodulation and demultiplexing. We deduce from this model a MAP estimate of the navigation message and of the signal SNR. In our case the signal model is a piecewise stationary process with change instants at bit edge position. We present preliminary SNR measurement with this technique for the discrimination of water and humid sand.
{"title":"Beach soil moisture measurement with a land reflected GPS bistatic radar technique","authors":"Q. Li, S. Reboul, S. Boutoille, J. Choquel, M. Benjelloun, A. Gardel","doi":"10.1109/PASSIVE.2008.4787002","DOIUrl":"https://doi.org/10.1109/PASSIVE.2008.4787002","url":null,"abstract":"In this work we investigate the potential for sensing beach soil moisture with the L band GPS bistatic radar concept. Characterisation of sediment surface (properties like humidity) is indeed important to better understand morphodynamic activity of intertidal part of beaches. In our approach we compare the direct GPS Signal to Noise Ratio with the reflected one in order to measure the soil moisture. We use a bit grabber to digitize and store the GPS L1 carrier (1.5 Ghz) samples. In this context the signal processing is off-line. In this work we proposed a model of the received signal after demodulation and demultiplexing. We deduce from this model a MAP estimate of the navigation message and of the signal SNR. In our case the signal model is a piecewise stationary process with change instants at bit edge position. We present preliminary SNR measurement with this technique for the discrimination of water and humid sand.","PeriodicalId":153349,"journal":{"name":"2008 New Trends for Environmental Monitoring Using Passive Systems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126664712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-10-01DOI: 10.1109/PASSIVE.2008.4786978
F. Caudal, H. Glotin
This paper discusses on estimating the behavior of a sperm whale using hydrophones recordings thanks to a set of features extracted from a real-time passive underwater acoustic tracking algorithm for multiple emitting whales. Acoustic localization permits to study whales' behavior in deep water (several hundreds of meters) without infering with the environment. Here, we use a real-time multiple tracking algorithm, which provides a localization of one or several sperm whales. Thanks to the positions coordinates and the audio files, we are able to automatically label the signal and to extract different features such as the speed, energy of the clicks, inter-click-interval (ICI)... These features allow us to cross-analyse the whale behavior (foraging , hunting, ingestion) and to see the influence of each parameters and the dependency between them. Finally, we generate a XML file for description and efficient access of deep ocean sound records for cetacean studies, which leads to index and structure the audio files. Thus, the behavior study is facilitated choosing and accessing the corresponding index in the recording. The complete method is processed on real data from the NUWC1 and the AUTEC2. As an illustration, we process the algorithm on a one whale case and study the correlation between the features and the whale behavior during the diving.
{"title":"High level automatic structuration of ocean passive data : From click sequence modulations to whale behavior analyses","authors":"F. Caudal, H. Glotin","doi":"10.1109/PASSIVE.2008.4786978","DOIUrl":"https://doi.org/10.1109/PASSIVE.2008.4786978","url":null,"abstract":"This paper discusses on estimating the behavior of a sperm whale using hydrophones recordings thanks to a set of features extracted from a real-time passive underwater acoustic tracking algorithm for multiple emitting whales. Acoustic localization permits to study whales' behavior in deep water (several hundreds of meters) without infering with the environment. Here, we use a real-time multiple tracking algorithm, which provides a localization of one or several sperm whales. Thanks to the positions coordinates and the audio files, we are able to automatically label the signal and to extract different features such as the speed, energy of the clicks, inter-click-interval (ICI)... These features allow us to cross-analyse the whale behavior (foraging , hunting, ingestion) and to see the influence of each parameters and the dependency between them. Finally, we generate a XML file for description and efficient access of deep ocean sound records for cetacean studies, which leads to index and structure the audio files. Thus, the behavior study is facilitated choosing and accessing the corresponding index in the recording. The complete method is processed on real data from the NUWC1 and the AUTEC2. As an illustration, we process the algorithm on a one whale case and study the correlation between the features and the whale behavior during the diving.","PeriodicalId":153349,"journal":{"name":"2008 New Trends for Environmental Monitoring Using Passive Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133073471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-10-01DOI: 10.1109/PASSIVE.2008.4786973
S. Harari
Localisation of underwater vehicles is usually accomplished by doing analog goniometry. If the number of microphones is high enough precision the process can be sufficient for an adequate signal to noise ratio. In underwater environments the signal to noise ratio decreases rapidly with distance. Furthermore measuring the SNR introduces noise. This limits the use of this technique.
{"title":"Active digital goniometry, principles and results","authors":"S. Harari","doi":"10.1109/PASSIVE.2008.4786973","DOIUrl":"https://doi.org/10.1109/PASSIVE.2008.4786973","url":null,"abstract":"Localisation of underwater vehicles is usually accomplished by doing analog goniometry. If the number of microphones is high enough precision the process can be sufficient for an adequate signal to noise ratio. In underwater environments the signal to noise ratio decreases rapidly with distance. Furthermore measuring the SNR introduces noise. This limits the use of this technique.","PeriodicalId":153349,"journal":{"name":"2008 New Trends for Environmental Monitoring Using Passive Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126982879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-10-01DOI: 10.1109/PASSIVE.2008.4786983
F. Chaillan
This study deals with the passive SONAR signal background spectral estimation. Practically, this processing is necessary to detect acoustic vibration from the data gathered by that kind of device. These phenomena appear as peaks on the estimated spectra of the collected data. That's why a decision test is applied on the estimated power spectral density. In order to ensure a constant false alarm rate of the detector, one needs to normalize the spectra, i.e. split each spectrum into three parts: the peaks, the background and a superimposed noise. Among the whole different technique developed during the last decades, the processing presented in this paper is the robust Kalman filter, an EM processing where the E step is a Kalman filter step and the M step is a dynamical system parameters estimation. This framework presents the interest to be real time and full automated, and not signal dependent, as long as the system initial guess remains physically realistic. Experimentations on simulated data and real world data are presented.
{"title":"Background spectrum estimation via robust Kalman filtering","authors":"F. Chaillan","doi":"10.1109/PASSIVE.2008.4786983","DOIUrl":"https://doi.org/10.1109/PASSIVE.2008.4786983","url":null,"abstract":"This study deals with the passive SONAR signal background spectral estimation. Practically, this processing is necessary to detect acoustic vibration from the data gathered by that kind of device. These phenomena appear as peaks on the estimated spectra of the collected data. That's why a decision test is applied on the estimated power spectral density. In order to ensure a constant false alarm rate of the detector, one needs to normalize the spectra, i.e. split each spectrum into three parts: the peaks, the background and a superimposed noise. Among the whole different technique developed during the last decades, the processing presented in this paper is the robust Kalman filter, an EM processing where the E step is a Kalman filter step and the M step is a dynamical system parameters estimation. This framework presents the interest to be real time and full automated, and not signal dependent, as long as the system initial guess remains physically realistic. Experimentations on simulated data and real world data are presented.","PeriodicalId":153349,"journal":{"name":"2008 New Trends for Environmental Monitoring Using Passive Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123165799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-10-01DOI: 10.1109/PASSIVE.2008.4787008
C. Ioana, A. Quinquis, Bertrand Gottin
The characterization of a natural environment (underwater, for example) and the identification of radar/communication signals in SIGINT (signal intelligence) are just two typical examples of applications requiring signal analysis in a passive configuration. In the first case, even if the characterization is based on the analysis of received signals in an active configuration, the unknown deformations of the transmitted signal transform the signal processing problem in a passive context one. Concerning the second case, the passive behavior of the signal intelligence field is a well-known problem in the electronic warfare problem.In this paper we propose a general signal analysis framework in passive context. We show that, in spite of the differences between some possible passive applications (underwater channel characterization and SIGINT) a unified signal analysis framework can defined. This definition starts from the general observation that real life signals received in a passive configuration are non-stationary. Their analysis in the time-frequency domain is well adapted so that it offers appropriated structures which are good candidates for the information post-processing. In a passive context, the definition of an appropriate time-frequency representation space is a complex problem, mainly related to the lack of a priori information about the processed signal. One general solution is proposed in this paper and it is based on the time-frequency-phase coherence. Conceptually, while the received signals are unknown (a model is difficult to be assumed), a general remark is the coherent shapes of their time-frequency structures. This coherence could be materialized by fundamental physical parameter of every signal - amplitude, time, frequency and initial phase. Indeed, the signal analysis framework is defined through three blocks : detection of regions of interest, segmentation and separation, analytical characterization. This architecture is mainly based on joint use of time, frequency and local phase analysis. More precisely, the phase information will be locally analysed, using generalized instantaneous moments, on the time-frequency regions previously selected thanks to the time-frequency grouping algorithm. This architecture constitutes an efficient scheme to solve the constraints brought by this type of signals with a complex time-frequency behavior and by the human operator to reduce his tasks in the decision process. Examples from underwater behavior (underwater mammals vocalizations) and electronic warfare will prove the efficiency of the proposed approach.
{"title":"Time-frequency-phase coherence - general framework for signal analysis in passive context","authors":"C. Ioana, A. Quinquis, Bertrand Gottin","doi":"10.1109/PASSIVE.2008.4787008","DOIUrl":"https://doi.org/10.1109/PASSIVE.2008.4787008","url":null,"abstract":"The characterization of a natural environment (underwater, for example) and the identification of radar/communication signals in SIGINT (signal intelligence) are just two typical examples of applications requiring signal analysis in a passive configuration. In the first case, even if the characterization is based on the analysis of received signals in an active configuration, the unknown deformations of the transmitted signal transform the signal processing problem in a passive context one. Concerning the second case, the passive behavior of the signal intelligence field is a well-known problem in the electronic warfare problem.In this paper we propose a general signal analysis framework in passive context. We show that, in spite of the differences between some possible passive applications (underwater channel characterization and SIGINT) a unified signal analysis framework can defined. This definition starts from the general observation that real life signals received in a passive configuration are non-stationary. Their analysis in the time-frequency domain is well adapted so that it offers appropriated structures which are good candidates for the information post-processing. In a passive context, the definition of an appropriate time-frequency representation space is a complex problem, mainly related to the lack of a priori information about the processed signal. One general solution is proposed in this paper and it is based on the time-frequency-phase coherence. Conceptually, while the received signals are unknown (a model is difficult to be assumed), a general remark is the coherent shapes of their time-frequency structures. This coherence could be materialized by fundamental physical parameter of every signal - amplitude, time, frequency and initial phase. Indeed, the signal analysis framework is defined through three blocks : detection of regions of interest, segmentation and separation, analytical characterization. This architecture is mainly based on joint use of time, frequency and local phase analysis. More precisely, the phase information will be locally analysed, using generalized instantaneous moments, on the time-frequency regions previously selected thanks to the time-frequency grouping algorithm. This architecture constitutes an efficient scheme to solve the constraints brought by this type of signals with a complex time-frequency behavior and by the human operator to reduce his tasks in the decision process. Examples from underwater behavior (underwater mammals vocalizations) and electronic warfare will prove the efficiency of the proposed approach.","PeriodicalId":153349,"journal":{"name":"2008 New Trends for Environmental Monitoring Using Passive Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117082919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-10-01DOI: 10.1109/PASSIVE.2008.4787000
D. O’Hagan, C. Baker
We present a system characterisation of a passive bistatic radar (PBR). The system under investigation exploits dasiailluminators of opportunitypsila, which in this case are commercial, non-cooperative, VHF FM broadcast transmissions. The PBR under investigation demonstrates the detection of large passenger-jet aircraft in the airspace over greater London. FM based PBRs such as the type examined here have been shown to be effective at remote sensing of auroral turbulence, density irregularities in the E-region and F-region of the ionosphere and meteor trails. Detection of aircraft is an important step in attempting to remotely sense outer-atmospheric phenomena as aircraft scattered power is of a comparable magnitude and similar Doppler frequency to the natural phenomena described. This paper also analyses the merits of FM broadcast transmissions for use as radar signals. A system characterisation with performance predictions is presented. The results show that target detections have been achieved to ranges in excess of 70 km (bistatic range). Multiple broadcast channels from two different transmitters of opportunity enhance the case for deciding whether or not targets are present. Air-truth data provided by a mode S/ADS-B IFF receiver is used for comparison with the 2-D bistatic results.
{"title":"Passive Bistatic Radar (PBR) using FM radio illuminators of opportunity","authors":"D. O’Hagan, C. Baker","doi":"10.1109/PASSIVE.2008.4787000","DOIUrl":"https://doi.org/10.1109/PASSIVE.2008.4787000","url":null,"abstract":"We present a system characterisation of a passive bistatic radar (PBR). The system under investigation exploits dasiailluminators of opportunitypsila, which in this case are commercial, non-cooperative, VHF FM broadcast transmissions. The PBR under investigation demonstrates the detection of large passenger-jet aircraft in the airspace over greater London. FM based PBRs such as the type examined here have been shown to be effective at remote sensing of auroral turbulence, density irregularities in the E-region and F-region of the ionosphere and meteor trails. Detection of aircraft is an important step in attempting to remotely sense outer-atmospheric phenomena as aircraft scattered power is of a comparable magnitude and similar Doppler frequency to the natural phenomena described. This paper also analyses the merits of FM broadcast transmissions for use as radar signals. A system characterisation with performance predictions is presented. The results show that target detections have been achieved to ranges in excess of 70 km (bistatic range). Multiple broadcast channels from two different transmitters of opportunity enhance the case for deciding whether or not targets are present. Air-truth data provided by a mode S/ADS-B IFF receiver is used for comparison with the 2-D bistatic results.","PeriodicalId":153349,"journal":{"name":"2008 New Trends for Environmental Monitoring Using Passive Systems","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124827551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-10-01DOI: 10.1109/PASSIVE.2008.4786994
I. Urazghildiiev, C. Clark, T. Krein
The problem of detecting and recognizing the sounds of fin whales, Balaenoptera physalus, and North Atlantic right whales, Eubalaena glacialis, in the presence ambient noise is considered. A proposed solution is based on a multiple-stage hypothesis-testing technique. The closed form representations of the algorithms are derived, and realizable detection schemes are developed. Empirical tests were conducted using data recordings collected in 2007 off the coast of Massachusetts. Results reveal that the proposed technique is able to detect approximately 80% of the calls detected by the human operator and to produce an average of 12.0 - 33.5 false alarms per 24 h of observation.
{"title":"Acoustic detection and recognition of fin whale and North Atlantic right whale sounds","authors":"I. Urazghildiiev, C. Clark, T. Krein","doi":"10.1109/PASSIVE.2008.4786994","DOIUrl":"https://doi.org/10.1109/PASSIVE.2008.4786994","url":null,"abstract":"The problem of detecting and recognizing the sounds of fin whales, Balaenoptera physalus, and North Atlantic right whales, Eubalaena glacialis, in the presence ambient noise is considered. A proposed solution is based on a multiple-stage hypothesis-testing technique. The closed form representations of the algorithms are derived, and realizable detection schemes are developed. Empirical tests were conducted using data recordings collected in 2007 off the coast of Massachusetts. Results reveal that the proposed technique is able to detect approximately 80% of the calls detected by the human operator and to produce an average of 12.0 - 33.5 false alarms per 24 h of observation.","PeriodicalId":153349,"journal":{"name":"2008 New Trends for Environmental Monitoring Using Passive Systems","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124907970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-10-01DOI: 10.1109/PASSIVE.2008.4787004
C. Waldmann, A. Nikolovska
With the growing concern in regard to melting ice caps there is a need of tracking iceberg calving events in the arctic seas. Acoustic detection of underwater signals is promising high sensitivity in this context and will supplement existing measurements with land based and underwater seismometers. The relevance of this measurements for the quantification of melting processes will depend on the technical realisation scenarios, the methods that are available to localise and quantify the sources of the according multiple sound transmitters in the arctic environment and finally the choice of the observation sites. This paper will describe the current status of knowledge in this field and anticipated concept to monitor ice cracking events with acoustic methods.
{"title":"Acoustic detection of ice cracking events","authors":"C. Waldmann, A. Nikolovska","doi":"10.1109/PASSIVE.2008.4787004","DOIUrl":"https://doi.org/10.1109/PASSIVE.2008.4787004","url":null,"abstract":"With the growing concern in regard to melting ice caps there is a need of tracking iceberg calving events in the arctic seas. Acoustic detection of underwater signals is promising high sensitivity in this context and will supplement existing measurements with land based and underwater seismometers. The relevance of this measurements for the quantification of melting processes will depend on the technical realisation scenarios, the methods that are available to localise and quantify the sources of the according multiple sound transmitters in the arctic environment and finally the choice of the observation sites. This paper will describe the current status of knowledge in this field and anticipated concept to monitor ice cracking events with acoustic methods.","PeriodicalId":153349,"journal":{"name":"2008 New Trends for Environmental Monitoring Using Passive Systems","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115261198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-10-01DOI: 10.1109/PASSIVE.2008.4787005
O. Gérard, S. Coraluppi, C. Carthel
This study shows the variation in Blainville's beaked whale buzz click characteristics. Due to the lack of statistical consistency, single-click classification appears infeasible. Nonetheless, the spectrum is very similar from one click to the next. Thanks to this slow variation it is possible to associate clicks using automatic tracking techniques [1]. Subsequently, tracks can be classified as buzzes based on the inter-click intervals.
{"title":"Analysis and classification of beaked whale buzz clicks","authors":"O. Gérard, S. Coraluppi, C. Carthel","doi":"10.1109/PASSIVE.2008.4787005","DOIUrl":"https://doi.org/10.1109/PASSIVE.2008.4787005","url":null,"abstract":"This study shows the variation in Blainville's beaked whale buzz click characteristics. Due to the lack of statistical consistency, single-click classification appears infeasible. Nonetheless, the spectrum is very similar from one click to the next. Thanks to this slow variation it is possible to associate clicks using automatic tracking techniques [1]. Subsequently, tracks can be classified as buzzes based on the inter-click intervals.","PeriodicalId":153349,"journal":{"name":"2008 New Trends for Environmental Monitoring Using Passive Systems","volume":"38 06 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116537450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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