Pub Date : 2006-07-12DOI: 10.1109/SAM.2006.1706217
M. Sasso, M. Talmant, G. Haiat, P. Laugier, S. Naili
The use of multi-dimensional wave extraction algorithm for a multi-receivers axial transmission ultrasound device used in bone evaluation is proposed. As far as we know, multi-dimensional signal processing techniques have never been implemented in this configuration. A SVD-based wavefront extraction is implemented for the characterization of an energetic low frequency contribution. Velocity accuracy is estimated on a synthetic dataset. Furthermore, the energetic low frequency removal is illustrated on in vivo signals. Results are promising as for the application of multi-dimensional techniques in medical ultrasound used in transmission
{"title":"Development of a Multi-Dimensional SVD based Technique for Multi-Receivers Ultrasound used in Bone Status Characterization","authors":"M. Sasso, M. Talmant, G. Haiat, P. Laugier, S. Naili","doi":"10.1109/SAM.2006.1706217","DOIUrl":"https://doi.org/10.1109/SAM.2006.1706217","url":null,"abstract":"The use of multi-dimensional wave extraction algorithm for a multi-receivers axial transmission ultrasound device used in bone evaluation is proposed. As far as we know, multi-dimensional signal processing techniques have never been implemented in this configuration. A SVD-based wavefront extraction is implemented for the characterization of an energetic low frequency contribution. Velocity accuracy is estimated on a synthetic dataset. Furthermore, the energetic low frequency removal is illustrated on in vivo signals. Results are promising as for the application of multi-dimensional techniques in medical ultrasound used in transmission","PeriodicalId":272327,"journal":{"name":"Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006.","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115296786","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 : 2006-07-12DOI: 10.1109/SAM.2006.1706160
K. Frampton, J. Lafuse, J. Aloi, M. Brown
Essex has developed a prototype hybrid optical/digital processor for range-Doppler image formation using wideband arbitrary waveforms. The processor is called the advanced optical processor (AOP) and is a hybrid acousto-optic/digital processor that generates high dynamic range, range-Doppler images from wideband radar returns in real time. The AOP was first tested at a U.S. Government facility in November 2005. The AOP is currently scheduled to be tested with a range radar in April 2006. The laboratory testing included three waveform types and verification of all the necessary trigger control signals. The range radar testing will include collection and processing of the same three waveform signals to demonstrate arbitrary waveform capability. The AOP supports high resolution processing necessary for target discrimination and kill assessment by enabling the use of true arbitrary wideband waveforms. The selected architecture combines the advantages of both optical signal processing for the front-end receiver and high-speed digital signal processing for the real-time processing. Its size is a 6U form-factor and fits within the 6U electronic chassis
{"title":"Advanced Optical Processor for Arbitrary Waveform Radar Imaging","authors":"K. Frampton, J. Lafuse, J. Aloi, M. Brown","doi":"10.1109/SAM.2006.1706160","DOIUrl":"https://doi.org/10.1109/SAM.2006.1706160","url":null,"abstract":"Essex has developed a prototype hybrid optical/digital processor for range-Doppler image formation using wideband arbitrary waveforms. The processor is called the advanced optical processor (AOP) and is a hybrid acousto-optic/digital processor that generates high dynamic range, range-Doppler images from wideband radar returns in real time. The AOP was first tested at a U.S. Government facility in November 2005. The AOP is currently scheduled to be tested with a range radar in April 2006. The laboratory testing included three waveform types and verification of all the necessary trigger control signals. The range radar testing will include collection and processing of the same three waveform signals to demonstrate arbitrary waveform capability. The AOP supports high resolution processing necessary for target discrimination and kill assessment by enabling the use of true arbitrary wideband waveforms. The selected architecture combines the advantages of both optical signal processing for the front-end receiver and high-speed digital signal processing for the real-time processing. Its size is a 6U form-factor and fits within the 6U electronic chassis","PeriodicalId":272327,"journal":{"name":"Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006.","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127452769","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 : 2006-07-12DOI: 10.1109/SAM.2006.1706101
Mohamed Sahmoudi, H. Boumaraf, M. Amin, D. Pham
In this paper, we introduce new time-varying fractional spectral matrices to exploit both the nonstationarity and heavy-tailed sources properties for blind separation of convolutive audio mixtures. We define these spectrum matrices, that are different for various delays, using fractional lower order statistics (FLOS) of data. Similar to the second order statistics (SOS) based approaches, we maximize the sources independence by jointly diagonalizing these fractional matrices spectrum of the reconstructed signals using a mutual information criterion. A set of experiments using audio signals and real impulse response of acoustic room are designed to verify the usefulness of the proposed method
{"title":"Blind Separation of Convolutive Mixtures using Nonstationarity and Fractional Lower Order Statistics (FLOS): Application to Audio Signals","authors":"Mohamed Sahmoudi, H. Boumaraf, M. Amin, D. Pham","doi":"10.1109/SAM.2006.1706101","DOIUrl":"https://doi.org/10.1109/SAM.2006.1706101","url":null,"abstract":"In this paper, we introduce new time-varying fractional spectral matrices to exploit both the nonstationarity and heavy-tailed sources properties for blind separation of convolutive audio mixtures. We define these spectrum matrices, that are different for various delays, using fractional lower order statistics (FLOS) of data. Similar to the second order statistics (SOS) based approaches, we maximize the sources independence by jointly diagonalizing these fractional matrices spectrum of the reconstructed signals using a mutual information criterion. A set of experiments using audio signals and real impulse response of acoustic room are designed to verify the usefulness of the proposed method","PeriodicalId":272327,"journal":{"name":"Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124831966","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 : 2006-07-12DOI: 10.1109/SAM.2006.1706147
R. Alizadeh, H. Amindavar, N. Granpayeh
Based on the nonlinear approximation of Huygens-Fresnel diffraction patterns, the SAR images of a target can be made up from a knowledge of a hologram for all frequencies and all aspects angles to provide a complete description of the target. In this paper we reconstruct the image of hologram employing the multiresolution Fresnelet transform to approximate the Huygens-Fresnel diffraction patterns in an off-axis geometry from the simulated test pattern (3bar). Fresnel transform is a wavelet-like transform, very close to Gabor functions (M. Unser et al., 1992) and well localized with respect to the holographic process. This method allows us to generate and reconstruct hologram on a digital computer, and apply multiresolution wavelet base analysis and special filtering on it. Since images are nonstationary process, we use fractional Brownian motion (fBm) method to describe texture in SAR images. It is known as a suitable model to classify a vast number of natural phenomena and shapes, such as the range of rivers, terrain surfaces, mountains ripples of water, coastlines and etc. The novelty of this technique lies in the use of Fresnel transform in reconstruction of holographic SAR images and fBm model for classifying them
基于惠更斯-菲涅耳衍射图样的非线性近似，可以从全息图的所有频率和所有角度合成目标的SAR图像，以提供目标的完整描述。本文采用多分辨率Fresnelet变换来近似惠更斯-菲涅耳衍射图样的离轴几何形状，重建全息图图像。菲涅耳变换是一种类小波变换，非常接近Gabor函数(M. Unser et al.， 1992)，并且相对于全息过程具有很好的局部化。该方法可以在数字计算机上生成和重建全息图，并对其进行多分辨率小波基分析和特殊滤波。由于图像是非平稳过程，我们使用分数布朗运动(fBm)方法来描述SAR图像的纹理。它被认为是一种适合对大量自然现象和形状进行分类的模型，例如河流的范围、地形表面、山脉、水的波纹、海岸线等。该技术的新颖之处在于利用菲涅耳变换对全息SAR图像进行重建，并利用fBm模型对其进行分类
{"title":"A Novel Non-Linear Approximation to the Huygens-Fresnel Diffraction Patterns for Reconstructing Digital Holographic SAR Images","authors":"R. Alizadeh, H. Amindavar, N. Granpayeh","doi":"10.1109/SAM.2006.1706147","DOIUrl":"https://doi.org/10.1109/SAM.2006.1706147","url":null,"abstract":"Based on the nonlinear approximation of Huygens-Fresnel diffraction patterns, the SAR images of a target can be made up from a knowledge of a hologram for all frequencies and all aspects angles to provide a complete description of the target. In this paper we reconstruct the image of hologram employing the multiresolution Fresnelet transform to approximate the Huygens-Fresnel diffraction patterns in an off-axis geometry from the simulated test pattern (3bar). Fresnel transform is a wavelet-like transform, very close to Gabor functions (M. Unser et al., 1992) and well localized with respect to the holographic process. This method allows us to generate and reconstruct hologram on a digital computer, and apply multiresolution wavelet base analysis and special filtering on it. Since images are nonstationary process, we use fractional Brownian motion (fBm) method to describe texture in SAR images. It is known as a suitable model to classify a vast number of natural phenomena and shapes, such as the range of rivers, terrain surfaces, mountains ripples of water, coastlines and etc. The novelty of this technique lies in the use of Fresnel transform in reconstruction of holographic SAR images and fBm model for classifying them","PeriodicalId":272327,"journal":{"name":"Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006.","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123297860","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 : 2006-07-12DOI: 10.1109/SAM.2006.1706092
Cheol-Sun Park, W. Jang, Daeyoung Kim
The resolving ambiguity of phase interferometer is necessary when the baseline separation between elements exceeds half wavelength since the phase difference between elements can only be measured modulo 2pi. It is difficult to meet the condition the minimum distance between two antennas is less than half wavelength for avoiding ambiguity in wideband operation. In this paper, we propose a simple and efficient array design method which minimizes the probability of ambiguity. This method adapts NLA (nonuniform linear array) geometry. And there is no need to maintain the distance between antennas less than half wavelength. We also show some numerical examples and experimental results of the 2-D array prototype for airborne application
{"title":"The Array Geometry Design in Airborne Microwave 2-D Direction Finding","authors":"Cheol-Sun Park, W. Jang, Daeyoung Kim","doi":"10.1109/SAM.2006.1706092","DOIUrl":"https://doi.org/10.1109/SAM.2006.1706092","url":null,"abstract":"The resolving ambiguity of phase interferometer is necessary when the baseline separation between elements exceeds half wavelength since the phase difference between elements can only be measured modulo 2pi. It is difficult to meet the condition the minimum distance between two antennas is less than half wavelength for avoiding ambiguity in wideband operation. In this paper, we propose a simple and efficient array design method which minimizes the probability of ambiguity. This method adapts NLA (nonuniform linear array) geometry. And there is no need to maintain the distance between antennas less than half wavelength. We also show some numerical examples and experimental results of the 2-D array prototype for airborne application","PeriodicalId":272327,"journal":{"name":"Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006.","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115105504","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 : 2006-07-12DOI: 10.1109/SAM.2006.1706173
L. Magagni, D. Gennaretti, M. Nicolini, M. Sergio, R. Guerrieri, R. Canegallo
Monitoring harsh environments such as underwater scenarios or aircraft external surfaces pertains to important applications like assisted navigation and tactical surveillance; nevertheless, it poses additional challenges compared with standard applications. At Transducers2005 we presented a wired addressing architecture of distributed sensors for monitoring real-time in-situ pressure variations in underwater environment that faces the above-mentioned issues. This architecture consists in a double array of identical and interconnected smart nodes monitoring a matrix of passive sensors. In this paper, we present an analysis of the delay model related to the presented architecture and a calculation of the overall frame-rate of the system as a function of the geometrical topology of the arrays. The topology of the network, i.e. the length of each bus and the number of nodes, can be chosen according to the application, and directly affects the global capacitive load on the serial lines. Each serial line can be schematized with a distributed RC model for the flat cable plus a lumped capacitance for each smart node. Then, a 3rd-order pi-segmented model of O'Brien-Savarino is calculated for a 16-block line with block length equal to 0.3 m. Thanks to that, the global time per iteration is calculated on each bus as well as the scanning time of the whole matrix and the frame rate for the system as a function of sensor distribution and of the aspect ratio of the matrix. This model can be employed to identify the optimal arrangement for the sensor matrix and smart node arrays
{"title":"Model for a Smart Network Monitoring a Wired Sensor Matrix","authors":"L. Magagni, D. Gennaretti, M. Nicolini, M. Sergio, R. Guerrieri, R. Canegallo","doi":"10.1109/SAM.2006.1706173","DOIUrl":"https://doi.org/10.1109/SAM.2006.1706173","url":null,"abstract":"Monitoring harsh environments such as underwater scenarios or aircraft external surfaces pertains to important applications like assisted navigation and tactical surveillance; nevertheless, it poses additional challenges compared with standard applications. At Transducers2005 we presented a wired addressing architecture of distributed sensors for monitoring real-time in-situ pressure variations in underwater environment that faces the above-mentioned issues. This architecture consists in a double array of identical and interconnected smart nodes monitoring a matrix of passive sensors. In this paper, we present an analysis of the delay model related to the presented architecture and a calculation of the overall frame-rate of the system as a function of the geometrical topology of the arrays. The topology of the network, i.e. the length of each bus and the number of nodes, can be chosen according to the application, and directly affects the global capacitive load on the serial lines. Each serial line can be schematized with a distributed RC model for the flat cable plus a lumped capacitance for each smart node. Then, a 3rd-order pi-segmented model of O'Brien-Savarino is calculated for a 16-block line with block length equal to 0.3 m. Thanks to that, the global time per iteration is calculated on each bus as well as the scanning time of the whole matrix and the frame rate for the system as a function of sensor distribution and of the aspect ratio of the matrix. This model can be employed to identify the optimal arrangement for the sensor matrix and smart node arrays","PeriodicalId":272327,"journal":{"name":"Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006.","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114179152","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 : 2006-07-12DOI: 10.1109/SAM.2006.1706168
M. Hasan
In this paper generalizations of Sanger's learning rule for nondefinite matrices are explored. It is shown that the left and right principal components of any matrix can be computed so that these components upper triangulize the original matrix. We also modified the original Sanger's system to obtain new dynamical systems with a larger domain of attraction. Stability analysis for several Sanger's type systems for the standard and generalized principal, and minor component analyzers applied to nonsymmetric matrices is developed
{"title":"Sanger's Like Systems for Generalized Principal and Minor Component Analysis","authors":"M. Hasan","doi":"10.1109/SAM.2006.1706168","DOIUrl":"https://doi.org/10.1109/SAM.2006.1706168","url":null,"abstract":"In this paper generalizations of Sanger's learning rule for nondefinite matrices are explored. It is shown that the left and right principal components of any matrix can be computed so that these components upper triangulize the original matrix. We also modified the original Sanger's system to obtain new dynamical systems with a larger domain of attraction. Stability analysis for several Sanger's type systems for the standard and generalized principal, and minor component analyzers applied to nonsymmetric matrices is developed","PeriodicalId":272327,"journal":{"name":"Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122204442","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 : 2006-07-12DOI: 10.1109/SAM.2006.1706163
K. J. Sohn, Hongbin Li, B. Himed
We consider herein the problem of detecting a multichannel signal in the presence of spatially and temporally colored disturbance. A parametric generalized likelihood ratio test (GLRT) is developed by modeling the disturbance as a multichannel autoregressive (AR) process. The parametric GLRT differs from Kelly's widely known GLRT which does not utilize any parametric model for the disturbance signal. Maximum likelihood (ML) parameter estimation underlying the parametric GLRT is examined. It is shown that the ML estimator for the alternative hypothesis is non-linear and there exists no closed-form expression. An alternative asymptotic ML (AML) estimator is presented, which yields asymptotically optimum parameter estimates at a reduced complexity. The performance of the parametric GLRT is studied by considering challenging cases with limited or no training signals for parameter estimation. Such cases (especially when training is unavailable) are of great interest in detecting signals in heterogeneous, fast changing, or dense-target environments. Compared with the recently introduced parametric adaptive matched filter (PAMF) and parametric Rao detectors, the parametric GLRT achieves higher data efficiency, offering improved detection performance in general
{"title":"Parametric GLRT for Multichannel Adaptive Signal Detection","authors":"K. J. Sohn, Hongbin Li, B. Himed","doi":"10.1109/SAM.2006.1706163","DOIUrl":"https://doi.org/10.1109/SAM.2006.1706163","url":null,"abstract":"We consider herein the problem of detecting a multichannel signal in the presence of spatially and temporally colored disturbance. A parametric generalized likelihood ratio test (GLRT) is developed by modeling the disturbance as a multichannel autoregressive (AR) process. The parametric GLRT differs from Kelly's widely known GLRT which does not utilize any parametric model for the disturbance signal. Maximum likelihood (ML) parameter estimation underlying the parametric GLRT is examined. It is shown that the ML estimator for the alternative hypothesis is non-linear and there exists no closed-form expression. An alternative asymptotic ML (AML) estimator is presented, which yields asymptotically optimum parameter estimates at a reduced complexity. The performance of the parametric GLRT is studied by considering challenging cases with limited or no training signals for parameter estimation. Such cases (especially when training is unavailable) are of great interest in detecting signals in heterogeneous, fast changing, or dense-target environments. Compared with the recently introduced parametric adaptive matched filter (PAMF) and parametric Rao detectors, the parametric GLRT achieves higher data efficiency, offering improved detection performance in general","PeriodicalId":272327,"journal":{"name":"Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006.","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126660123","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 : 2006-07-12DOI: 10.1109/SAM.2006.1706108
O. Besson, L. Scharf, S. Kraut
We consider the problem of detecting a partially unknown signal, in the presence of unknown noise, using multiple snapshots in the primary data. To account for uncertainties about signal's signature, we assume that the steering vector lies on an unknown line in a known linear subspace. Additionally, we consider a partially homogeneous environment, for which the covariance matrix of the primary and the secondary data have the same structure, but possibly different levels. We study the invariances of the detection problem and derive the maximal invariant. A two-step generalized likelihood ratio test (GLRT) is formulated and compared with a 2-step GLRT which assumes that the steering vector is known
{"title":"Adaptive Matched Direction Detector","authors":"O. Besson, L. Scharf, S. Kraut","doi":"10.1109/SAM.2006.1706108","DOIUrl":"https://doi.org/10.1109/SAM.2006.1706108","url":null,"abstract":"We consider the problem of detecting a partially unknown signal, in the presence of unknown noise, using multiple snapshots in the primary data. To account for uncertainties about signal's signature, we assume that the steering vector lies on an unknown line in a known linear subspace. Additionally, we consider a partially homogeneous environment, for which the covariance matrix of the primary and the secondary data have the same structure, but possibly different levels. We study the invariances of the detection problem and derive the maximal invariant. A two-step generalized likelihood ratio test (GLRT) is formulated and compared with a 2-step GLRT which assumes that the steering vector is known","PeriodicalId":272327,"journal":{"name":"Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006.","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127789299","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 : 2006-07-12DOI: 10.1109/SAM.2006.1706218
J. De la Rosa, I. Lloret, Puntonet, J. Górriz
Two high-sensitivity ultrasonic transducers have been used to perform the higher-order characterization of vibratory events, in order to get the tracks of low-level transients produced when wood fibres are broken. Although the power spectral density is a valid tool for a prior characterization, third and fourth-order spectra slices exhibit more distinctive shapes, because they content a few number of frequency components, which have been enhanced over the thermal noise, which comes from the sensor and the equipment, and the external sources of interference. The wide-band transducer exhibits better performance due to the expanded spectral pattern it outlines. Fourth-order slices can be used as a complement to third-order ones, when the resolution in the bi-spectrum is not as much satisfactory.
{"title":"Wide-band transducers and higher-order spectral characterization of low-level ultrasounds in wood","authors":"J. De la Rosa, I. Lloret, Puntonet, J. Górriz","doi":"10.1109/SAM.2006.1706218","DOIUrl":"https://doi.org/10.1109/SAM.2006.1706218","url":null,"abstract":"Two high-sensitivity ultrasonic transducers have been used to perform the higher-order characterization of vibratory events, in order to get the tracks of low-level transients produced when wood fibres are broken. Although the power spectral density is a valid tool for a prior characterization, third and fourth-order spectra slices exhibit more distinctive shapes, because they content a few number of frequency components, which have been enhanced over the thermal noise, which comes from the sensor and the equipment, and the external sources of interference. The wide-band transducer exhibits better performance due to the expanded spectral pattern it outlines. Fourth-order slices can be used as a complement to third-order ones, when the resolution in the bi-spectrum is not as much satisfactory.","PeriodicalId":272327,"journal":{"name":"Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006.","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126215258","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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