Pub Date : 2008-07-21DOI: 10.1109/SAM.2008.4606821
V. Havary-Nassab, S. Shahbazpanahi, A. Grami, A. Gershman
In this paper, we use a 4times4 MIMO testbed to investigate the experimental performance of the blind channel estimation technique presented in (Shahbazpanahi et al., 2005). The operating frequency throughout all experiments was selected to be 2.47 GHz and the transmission bandwidth was 20 MHz. Our experimental results show that the performance of the blind technique can be very close to that of non-blind training based receiver which uses a significant bandwidth overhead as compared to the blind approach developed in (Shahbazpanahi et al., 2005).
在本文中，我们使用4times4 MIMO测试平台来研究(Shahbazpanahi et al.， 2005)中提出的盲信道估计技术的实验性能。所有实验的工作频率选择为2.47 GHz，传输带宽为20 MHz。我们的实验结果表明，与(Shahbazpanahi等人，2005)中开发的盲方法相比，盲技术的性能可以非常接近基于非盲训练的接收器，后者使用了显著的带宽开销。
{"title":"Experimental performance evaluation of blind channel estimation for orthogonal space-time block codes","authors":"V. Havary-Nassab, S. Shahbazpanahi, A. Grami, A. Gershman","doi":"10.1109/SAM.2008.4606821","DOIUrl":"https://doi.org/10.1109/SAM.2008.4606821","url":null,"abstract":"In this paper, we use a 4times4 MIMO testbed to investigate the experimental performance of the blind channel estimation technique presented in (Shahbazpanahi et al., 2005). The operating frequency throughout all experiments was selected to be 2.47 GHz and the transmission bandwidth was 20 MHz. Our experimental results show that the performance of the blind technique can be very close to that of non-blind training based receiver which uses a significant bandwidth overhead as compared to the blind approach developed in (Shahbazpanahi et al., 2005).","PeriodicalId":422747,"journal":{"name":"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130177864","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 : 2008-07-21DOI: 10.1109/SAM.2008.4606909
C. Schwarzl, D. Watzenig, C. Fox
Electrical capacitance tomography is targeted on estimating the spatial permittivity distribution of an inhomogeneous medium from measurements of trans-capacitance of a multi-electrode assembly outside the boundary of the medium. Since small changes in the measured data cause large or unbounded changes in recovered parameters, the problem is an ill-posed inverse problem. In this article, special focus is on the robust reconstruction of the shape of material inhomogeneities in an otherwise uniform background material. In order to represent the boundary of the inclusion, radial basis functions (RBF) implying a low order of the state-space are introduced. This approach ensures smooth contours how they appear in industrial applications like in oil refinement. The inverse problem is formulated in a Bayesian inferential framework, by specifying a prior distribution for the shape of the inclusion, and characterizing the statistics of measurement noise. The Markov chain Monte Carlo (MCMC) is presented to efficiently explore the posterior distribution. The applicability of the proposed MCMC sampler is verified for a reconstruction example using measured data.
{"title":"Estimation of contour parameter uncertainties in permittivity imaging using MCMC sampling","authors":"C. Schwarzl, D. Watzenig, C. Fox","doi":"10.1109/SAM.2008.4606909","DOIUrl":"https://doi.org/10.1109/SAM.2008.4606909","url":null,"abstract":"Electrical capacitance tomography is targeted on estimating the spatial permittivity distribution of an inhomogeneous medium from measurements of trans-capacitance of a multi-electrode assembly outside the boundary of the medium. Since small changes in the measured data cause large or unbounded changes in recovered parameters, the problem is an ill-posed inverse problem. In this article, special focus is on the robust reconstruction of the shape of material inhomogeneities in an otherwise uniform background material. In order to represent the boundary of the inclusion, radial basis functions (RBF) implying a low order of the state-space are introduced. This approach ensures smooth contours how they appear in industrial applications like in oil refinement. The inverse problem is formulated in a Bayesian inferential framework, by specifying a prior distribution for the shape of the inclusion, and characterizing the statistics of measurement noise. The Markov chain Monte Carlo (MCMC) is presented to efficiently explore the posterior distribution. The applicability of the proposed MCMC sampler is verified for a reconstruction example using measured data.","PeriodicalId":422747,"journal":{"name":"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127081145","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 : 2008-07-21DOI: 10.1109/SAM.2008.4606906
I. Thanasopoulos, J. Avaritsiotis
In this paper we propose a discrete wavelet transform (DWT) method for event detection and estimation of the time of arrival (TOA) of seismic signals in a sensor network. The Haar wavelet is selected for its low computational complexity and its good locality in time domain which is essential for the analysis of transient signals. The proposed method requires no a priori knowledge about the spectral characteristics of the signals, because the algorithm defines the optimum scales for the extraction of information by time-domain features as the signal is acquired. The performance of the algorithm is verified using a computer program that simulates the propagation of surface seismic waves. Simulation results corroborate the suitability of the proposed method for source localization applications.
{"title":"Seismic detection and time of arrival estimation in noisy environments based on the haar wavelet transform","authors":"I. Thanasopoulos, J. Avaritsiotis","doi":"10.1109/SAM.2008.4606906","DOIUrl":"https://doi.org/10.1109/SAM.2008.4606906","url":null,"abstract":"In this paper we propose a discrete wavelet transform (DWT) method for event detection and estimation of the time of arrival (TOA) of seismic signals in a sensor network. The Haar wavelet is selected for its low computational complexity and its good locality in time domain which is essential for the analysis of transient signals. The proposed method requires no a priori knowledge about the spectral characteristics of the signals, because the algorithm defines the optimum scales for the extraction of information by time-domain features as the signal is acquired. The performance of the algorithm is verified using a computer program that simulates the propagation of surface seismic waves. Simulation results corroborate the suitability of the proposed method for source localization applications.","PeriodicalId":422747,"journal":{"name":"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131073012","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 : 2008-07-21DOI: 10.1109/SAM.2008.4606814
A. Morshedi, M. Torlak
Polarization diversity is an interesting alternative to space diversity, but the channel characteristics need to be investigated. To evaluate the dual polarized channels, a 2times2 multiple-input-multiple-output (MIMO) wireless testbed has been developed. In addition, a dual polarized microstrip patch antenna array has been designed to be used as the transmitter and receiver in this system. Performance evaluation has been based on symbol error rate (SER) and channel gain. Channel measurements were conducted in line-of-sight (LOS) and non-line-of-sight (NLOS) indoor office environments. The results indicate that the dual polarized patch antennas are either comparable or better than the spatially separated patch antennas in terms of SER. The channel gains are more beneficial for vertical polarization in LOS and horizontal polarization in NLOS, but in both environments the dual polarized combination performs in between the space diversity schemes. Thus, if the receiver location changes environments, polarization diversity will yield favorable results.
{"title":"Experimental investigation of polarization diversity","authors":"A. Morshedi, M. Torlak","doi":"10.1109/SAM.2008.4606814","DOIUrl":"https://doi.org/10.1109/SAM.2008.4606814","url":null,"abstract":"Polarization diversity is an interesting alternative to space diversity, but the channel characteristics need to be investigated. To evaluate the dual polarized channels, a 2times2 multiple-input-multiple-output (MIMO) wireless testbed has been developed. In addition, a dual polarized microstrip patch antenna array has been designed to be used as the transmitter and receiver in this system. Performance evaluation has been based on symbol error rate (SER) and channel gain. Channel measurements were conducted in line-of-sight (LOS) and non-line-of-sight (NLOS) indoor office environments. The results indicate that the dual polarized patch antennas are either comparable or better than the spatially separated patch antennas in terms of SER. The channel gains are more beneficial for vertical polarization in LOS and horizontal polarization in NLOS, but in both environments the dual polarized combination performs in between the space diversity schemes. Thus, if the receiver location changes environments, polarization diversity will yield favorable results.","PeriodicalId":422747,"journal":{"name":"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128488423","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 : 2008-07-21DOI: 10.1109/SAM.2008.4606892
T. Habib, M. Képesi, L. Ottowitz
This paper proposes an enhancement and evaluates the performance of a recently proposed method for joint extraction of pitch and direction of arrival for speaker localization. We propose a new weighting function in order to suppress the cross-terms of the aforementioned method. The performance of the method is evaluated by measuring the correct estimate of position at a frame level. This evaluation analyzes the limits of the method at different background noise levels by using real world recordings. The results show that the proposed algorithm gives more consistent location estimates leading to a reduction in angular deviation by 4.23deg at -3 dB SNR.
{"title":"Experimental evaluation of the joint position-pitch estimation (POPI) algorithm in noisy environments","authors":"T. Habib, M. Képesi, L. Ottowitz","doi":"10.1109/SAM.2008.4606892","DOIUrl":"https://doi.org/10.1109/SAM.2008.4606892","url":null,"abstract":"This paper proposes an enhancement and evaluates the performance of a recently proposed method for joint extraction of pitch and direction of arrival for speaker localization. We propose a new weighting function in order to suppress the cross-terms of the aforementioned method. The performance of the method is evaluated by measuring the correct estimate of position at a frame level. This evaluation analyzes the limits of the method at different background noise levels by using real world recordings. The results show that the proposed algorithm gives more consistent location estimates leading to a reduction in angular deviation by 4.23deg at -3 dB SNR.","PeriodicalId":422747,"journal":{"name":"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134352931","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 : 2008-07-21DOI: 10.1109/SAM.2008.4606847
Pei-Jung Chung, Shuang Wan
The performance of most existing array processing algorithms relies heavily on the precise knowledge of array manifold, which is decided by individual sensor characteristics and array configuration. A major challenge for self-calibration techniques is the increased computational burden due to additional perturbation parameters. In this contribution, a novel procedure for array self-calibration is presented. We apply the well known numerical method, the Space Alternating Generalized EM algorithm (SAGE), to simplify the multi-dimensional search procedure required for finding maximum likelihood (ML) estimates. Simulation shows that the proposed algorithm outperforms existing methods that are based on the small perturbation assumption. Furthermore, the proposed algorithm remain robust in critical scenarios including large sensor position errors and closely located signals.
{"title":"Array self-calibration using SAGE algorithm","authors":"Pei-Jung Chung, Shuang Wan","doi":"10.1109/SAM.2008.4606847","DOIUrl":"https://doi.org/10.1109/SAM.2008.4606847","url":null,"abstract":"The performance of most existing array processing algorithms relies heavily on the precise knowledge of array manifold, which is decided by individual sensor characteristics and array configuration. A major challenge for self-calibration techniques is the increased computational burden due to additional perturbation parameters. In this contribution, a novel procedure for array self-calibration is presented. We apply the well known numerical method, the Space Alternating Generalized EM algorithm (SAGE), to simplify the multi-dimensional search procedure required for finding maximum likelihood (ML) estimates. Simulation shows that the proposed algorithm outperforms existing methods that are based on the small perturbation assumption. Furthermore, the proposed algorithm remain robust in critical scenarios including large sensor position errors and closely located signals.","PeriodicalId":422747,"journal":{"name":"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134317785","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 : 2008-07-21DOI: 10.1109/SAM.2008.4606905
K. Todros, J. Tabrikian
In this paper, a new lower bound on the mean-square-error of unbiased estimators of deterministic parameters is developed. The proposed bound is derived from a class of bounds presented in our recent work using the kernel of the Fourier transform, multiplied by a ldquoweightingrdquo function. The ldquoweightingrdquo function is defined on the parameter space and its significance in the parameter space and frequency domain is discussed throughout the paper. We show that the proposed bound is computationally manageable and can be easily implemented using the fast Fourier transform. The proposed bound is applied for the problem of direction-of-arrival estimation. It is shown by simulations that in comparison to other existing bounds in the literature, the proposed bound provides better prediction of the signal-to-noise ratio threshold region, exhibited by the maximum-likelihood estimator.
{"title":"A new lower bound based on weighted fourier transform of the likelihood ratio function","authors":"K. Todros, J. Tabrikian","doi":"10.1109/SAM.2008.4606905","DOIUrl":"https://doi.org/10.1109/SAM.2008.4606905","url":null,"abstract":"In this paper, a new lower bound on the mean-square-error of unbiased estimators of deterministic parameters is developed. The proposed bound is derived from a class of bounds presented in our recent work using the kernel of the Fourier transform, multiplied by a ldquoweightingrdquo function. The ldquoweightingrdquo function is defined on the parameter space and its significance in the parameter space and frequency domain is discussed throughout the paper. We show that the proposed bound is computationally manageable and can be easily implemented using the fast Fourier transform. The proposed bound is applied for the problem of direction-of-arrival estimation. It is shown by simulations that in comparison to other existing bounds in the literature, the proposed bound provides better prediction of the signal-to-noise ratio threshold region, exhibited by the maximum-likelihood estimator.","PeriodicalId":422747,"journal":{"name":"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132992829","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 : 2008-07-21DOI: 10.1109/SAM.2008.4606873
P. Honeine, Cédric Richard, Mehdi Essoloh, H. Snoussi
In this paper, we propose a new approach to sensor localization problems, based on recent developments in machine leaning. The main idea behind it is to consider a matrix regression method between the ranging matrix and the matrix of inner products between positions of sensors, in order to complete the latter. Once we have learnt this regression from information between sensors of known positions (beacons), we apply it to sensors of unknown positions. Retrieving the estimated positions of the latter can be done by solving a linear system. We propose a distributed algorithm, where each sensor positions itself with information available from its nearby beacons. The proposed method is validated by experimentations.
{"title":"Localization in sensor networks - A matrix regression approach","authors":"P. Honeine, Cédric Richard, Mehdi Essoloh, H. Snoussi","doi":"10.1109/SAM.2008.4606873","DOIUrl":"https://doi.org/10.1109/SAM.2008.4606873","url":null,"abstract":"In this paper, we propose a new approach to sensor localization problems, based on recent developments in machine leaning. The main idea behind it is to consider a matrix regression method between the ranging matrix and the matrix of inner products between positions of sensors, in order to complete the latter. Once we have learnt this regression from information between sensors of known positions (beacons), we apply it to sensors of unknown positions. Retrieving the estimated positions of the latter can be done by solving a linear system. We propose a distributed algorithm, where each sensor positions itself with information available from its nearby beacons. The proposed method is validated by experimentations.","PeriodicalId":422747,"journal":{"name":"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133491095","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 : 2008-07-21DOI: 10.1109/SAM.2008.4606885
Michael Rubsamen, A. Gershman
In this paper, two robust presteered broadband (PB) beamformers are developed using worst-case designs. The proposed techniques are shown to enjoy a reduced computational complexity and/or significant performance improvements as compared to the existing robust wideband beamforming techniques in scenarios with array response errors.
{"title":"Robust presteered broadband beamforming based on worst-case performance optimization","authors":"Michael Rubsamen, A. Gershman","doi":"10.1109/SAM.2008.4606885","DOIUrl":"https://doi.org/10.1109/SAM.2008.4606885","url":null,"abstract":"In this paper, two robust presteered broadband (PB) beamformers are developed using worst-case designs. The proposed techniques are shown to enjoy a reduced computational complexity and/or significant performance improvements as compared to the existing robust wideband beamforming techniques in scenarios with array response errors.","PeriodicalId":422747,"journal":{"name":"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122060269","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 : 2008-07-21DOI: 10.1109/SAM.2008.4606865
M. Moebus, A. Zoubir
We address the problem of sparse planar array design. Based on the theory of minimum redundancy arrays, we recently proposed an iterative algorithm that is capable to design highly thinned arrays with a low side-lobe level while retaining the half-power-beam-width of uniform arrays. In this paper, we analyze the effect of kernel bandwidth and compare the approach to a recent paper by Kopilovich which is based on the family of Hadamard difference sets. The results show that the proposed method achieves similar performance with a substantially lower amount of array elements. Side-Lobe-Levels are comparable to the ones from uniform arrays and only slightly higher than for Hadamard-based arrays.
{"title":"On the design of sparse arrays using difference sets","authors":"M. Moebus, A. Zoubir","doi":"10.1109/SAM.2008.4606865","DOIUrl":"https://doi.org/10.1109/SAM.2008.4606865","url":null,"abstract":"We address the problem of sparse planar array design. Based on the theory of minimum redundancy arrays, we recently proposed an iterative algorithm that is capable to design highly thinned arrays with a low side-lobe level while retaining the half-power-beam-width of uniform arrays. In this paper, we analyze the effect of kernel bandwidth and compare the approach to a recent paper by Kopilovich which is based on the family of Hadamard difference sets. The results show that the proposed method achieves similar performance with a substantially lower amount of array elements. Side-Lobe-Levels are comparable to the ones from uniform arrays and only slightly higher than for Hadamard-based arrays.","PeriodicalId":422747,"journal":{"name":"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123392731","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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