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检索条件"任意字段=Sensor Array and Multichannel Signal Processing Workshop"

共 2593 条记录，以下是191-200 订阅

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Iterative Sparse Through-the-Wall Imaging

Iterative Sparse Through-the-Wall Imaging

引用

IEEE 7th sensor array and multichannel signal processing workshop (SAM)

作者： Nikolic, Marija Nehorai, Arye Djordjevic, Antonije Univ Belgrade Sch Elect Engn Bulevar Kralja Aleksandra 73 Belgrade 11000 Serbia Washington Univ Dept Elect & Syst Engn St Louis MO 63130 USA

ISBN: (纸本)9781467310710

We consider iterative electromagnetic imaging of metallic targets hidden behind dielectric walls using sparse regularization. As in the equivalent-source method, we assume that the targets can be approximated by a set of filament currents whose locations are unknown. By using the iterative procedure, we reveal additional filament currents thus enlarging the target image. In order to take into account the mutual interaction between the current sources, and yet obtain the model amenable to signal processing, we combine the method of moments and the ray tracing.

关键词： target image Ray tracing Current sources Iterative Iterative Process METHOD OF MOMENTS Cytoskeletal Filaments signal processing Imaging

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A new beamformer based on phase dispersion to improve 2D sparse array response

A new beamformer based on phase dispersion to improve 2D spa...

引用

IEEE 7th sensor array and multichannel signal processing workshop (SAM)

作者： Martinez-Graullera, Oscar Romero-Laorden, David Ibanez, Alberto Ullate, Luis G. CAEND UPM CSIC Madrid 28006 Spain

ISBN: (纸本)9781467310710

This work studies a new beamformer for non-periodic sparse bidimensional ultrasonic array transducer. It is based on a weighting factor based on signals phase dispersion to enhance the image points where the phase coherence between the received signals is high. A method to measure the phase dispersion based on Fourier analysis and its integration in the beamformer are presented. Its performance is evaluated using a non-periodic 2D sparse array based on Fermat spiral with 96 elements and a diameter of 60 lambda. Compared with conventional Delay-And-Sum beamformer the proposed solution reduces the aperture lateral resolution and improves its dynamic range, achieving up to 50dB of contrast in the image and less 1 degrees in lateral resolution.

关键词： Fourier analysis

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MULTIVARIATE SPECTRAL RECONSTRUCTION OF STAP COVARIANCE MATRICES: HERMITIAN "RELAXATION" AND PERFORMANCE ANALYSIS

MULTIVARIATE SPECTRAL RECONSTRUCTION OF STAP COVARIANCE MATR...

引用

IEEE sensor array and multichannel signal processing workshop

作者： Abramovich, Yuri I. Johnson, Ben A. Spencer, Nicholas K. DSTO ISR Div Edinburgh Australia ITR Univ RLM Pty Ltd Edinburgh Australia DSTO ARI Pty Ltd Edinburgh Australia

ISBN: (纸本)9781424422401

In space-time adaptive processing (STAP) applications, temporally stationary clutter results in a Toeplitz-block clutter covariance matrix. In the reduced-order parametric matched filter STAP technique, this covariance matrix is reconstructed from a small number of estimated parameters, resulting in a much more efficient use of training samples. This paper explores a computationally advantageous "relaxed" maximum entropy (Burg) reconstruction technique which does not restore a strict Toeplitz-block structure, but does preserve the Burg spectrum. Performance of the reconstructed covariance matrix model as a STAP filter is evaluated using the DARPA KASSPER dataset and compared with "proper" Toeplitz-block reconstruction.

关键词： Toeplitz matrices covariance matrices autoregressive processes maximum entropy methods spacetime adaptive processing

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Mitigating Outliers for Bayesian Mixture of Factor Analyzers 11

Mitigating Outliers for Bayesian Mixture of Factor Analyzers

引用

IEEE 11th sensor array and multichannel signal processing workshop (SAM)

作者： Chen, Zhongtao Cheng, Lei Shenzhen Res Inst Big Data Shenzhen Peoples R China Chinese Univ Hong Kong Shenzhen Peoples R China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119465

The Bayesian mixture of factor analyzers (BMFA), which achieves joint clustering and dimensionality reduction, is with an appealing feature of automatic hyper-parameter learning. In addition to its great success in various unsupervised learning tasks, it exemplifies how the Bayesian statistics can be leveraged to achieve automatic hyper-parameter learning, which is an open problem of modern simultaneous (deep) dimensionality reduction and clustering. Due to the importance of the BMFA, in this paper, its mechanism is carefully investigated, and a robust variant of the BMFA that can mitigate potential outliers is further proposed. Numerical studies are presented to show the remarkable performance of the proposed algorithm in terms of accuracy and robustness.

关键词： Dimensionality reduction array signal processing Conferences signal processing algorithms Clustering algorithms Robustness Bayes methods

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MUSIC-Based array Imaging in Multi-Modal Ultrasonic Non-Destructive Testing

MUSIC-Based Array Imaging in Multi-Modal Ultrasonic Non-Dest...

引用

IEEE 7th sensor array and multichannel signal processing workshop (SAM)

作者： Foroozan, Foroohar ShahbazPanahi, Shahram Univ Ontario Inst Technol Fac Engn & Appl Sci Oshawa ON L1H 7K4 Canada

ISBN: (纸本)9781467310710

We propose a MUSIC based array imaging method for ultrasonic non-destructive testing (NDT) applications. We take the mode conversion phenomenon into account and develop a MUSIC-based imaging technique which exploits the additional information that is present in all propagating modes to the advantage of the imaging process-a problem not previously addressed in the context of NDT applications. Both the numerical simulations as well as data validation show that our proposed approach performs better than the traditional MUSIC based and delay-and-sum (DAS) based imaging algorithms in terms of root mean square error (RMSE) and also provides higher resolution and better side lobe suppression capabilities.

关键词： Ultrasonic array Imaging Multi-Modal Propagation Mode Conversion MUSIC DAS

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Toeplitz Structured Covariance Matrix Estimation for Radar Applications 11

Toeplitz Structured Covariance Matrix Estimation for Radar A...

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IEEE 11th sensor array and multichannel signal processing workshop (SAM)

作者： Du, Xiaolin Aubry, Augusto De Maio, Antonio Cui, Guolong Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu Peoples R China Yantai Univ Sch Comp & Control Engn Yantai Peoples R China Univ Napoli Federico II DIETI Naples Italy

ISBN: (纸本)9781728119465

Following a geometric paradigm, the estimation of a Toeplitz structured covariance matrix is considered. The estimator minimizes the distance from the Sample Covariance Matrix (SCM) while complying with some specific constraints modeling the covariance structure. The resulting constrained optimization problem is solved globally resorting to the Dykstra' projection framework. Each step of the procedure involves the solution of two convex sub-problems, whose minimizers are available in closed form. Simulation results related to typical radar environments highlight the effectiveness of the devised method.

关键词： Radar signal processing covariance matrix estimation projection Toeplitz structure

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MIMO Radar And Communications Spectrum Sharing: A Multiple-Access Perspective 10

MIMO Radar And Communications Spectrum Sharing: A Multiple-A...

引用

10th IEEE sensor array and multichannel signal processing workshop (SAM)

作者： Rong, Yu Chiriyath, Alex R. Bliss, Daniel W. Arizona State Univ Bliss Lab Informat Signals & Syst Tempe AZ 85287 USA

ISBN: (纸本)9781538647523

In this paper, we investigate the joint multiple-input multiple-output (MIMO) radar and communications system convergence problem and develop a joint radar-communications performance bound using the concept of estimation rate for radar system and data information rate for communications system. At the radar receiver, we propose a Successive Interference Cancellation (SIC) strategy to estimate radar parameters and decode communications signal simultaneously. While, at the MIMO communications transmitter, we propose a spectrum sharing scheme and show that the optimal communications performance can be achieved through a spectral and spatial waterfilling algorithm. In the end, we show that the Multiple-Access (MAC) performance bound outperforms the result from the spectrally isolated MIMO radar-communications system.

关键词： Radar Silicon carbide Estimation MIMO communication Radar signal processing"

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MMOSPA-based Direction-of-Arrival Estimation for Planar Antenna arrays

MMOSPA-based Direction-of-Arrival Estimation for Planar Ante...

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8th IEEE sensor array and multichannel signal processing workshop (SAM)

作者： Baum, Marcus Willett, Peter Hanebeck, Uwe D. Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA Karlsruhe Inst Technol KIT Intelligent Sensor Actuator Syst Lab ISAS Karlsruhe Germany

ISBN: (纸本)9781479914814

This work is concerned with direction-of-arrival (DOA) estimation of narrowband signals from multiple targets using a planar antenna array. We illustrate the shortcomings of Maximum Likelihood (ML), Maximum a Posteriori (MAP), and Minimum Mean Squared Error (MMSE) estimation, issues that can be attributed to the symmetry in the likelihood function that must exist when there is no information about labeling of targets. We proffer the recently introduced concept of Minimum Mean OSPA (MMOSPA) estimation that is based on the optimal sub-pattern assignment (OSPA) metric for sets and hence inherently incorporates symmetric likelihood functions.

关键词： planar antenna arrays Direction of arrival estimation Likelihood Functions Mean square error Narrowband Antenna arrays Targets SETTING Planar antennas

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Optimal Precoding Design for Decentralized Detection of Deterministic signals

Optimal Precoding Design for Decentralized Detection of Dete...

引用

IEEE 7th sensor array and multichannel signal processing workshop (SAM)

作者： Fang, Jun Li, Hongbin Chen, Zhi Li, Shaoqian Univ Elect Sci & Technol China Natl Key Lab Commun Chengdu 610054 Peoples R China Stevens Inst Technol Dept Elect & Comp Engn Hoboken NJ 07030 USA

ISBN: (纸本)9781467310710

We consider a decentralized detection problem in a power-constrained wireless sensor networks (WSNs), in which a number of sensor nodes collaborate to detect the presence of a deterministic vector signal. The signal to be detected is assumed known a priori. Each sensor conducts a local linear processing to convert its observations into one or multiple messages. The messages are conveyed to the fusion center (FC) by an uncoded amplify-and-forward scheme, where a global decision is made. Given a total network transmit power constraint, we investigate the optimal linear processing strategy for each sensor. Our study finds that the optimal linear precoder has the form of a matched filter. Depending on the channel characteristics, one or multiple versions of the filtered/compressed message should be reported to the FC.

关键词： Decentralized detection precoding design wireless sensor networks

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Wideband array signal processing using MCMC methods

Wideband array signal processing using MCMC methods

引用

2nd IEEE sensor array and multichannel signal processing workshop

作者： Ng, W Reilly, JP Kirubarajan, T Larocque, JR McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4K1 Canada

ISBN: (纸本)0780375513

This paper proposes a novel wideband structure for array signal processing. A new wideband model is formed where the observations are linear functions of the source amplitudes, but nonlinear in the direction of arrival (DOA) parameters. The method lends itself well to a Bayesian approach for jointly estimating the model order and the DOAs through a reversible jump Markov chain Monte Carlo (MCMC) procedure. The source amplitudes are estimated through a maximum a posteriori (MAP) procedure. The DOA estimation performance of the proposed method is compared with the theoretical Cramer-Rao lower bound (CRLB) for this problem. Simulation results demonstrate the effectiveness and robustness of the method.

关键词： Direction of arrival

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