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共 1267 条记录，以下是211-220 订阅

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Direction of Arrival Estimation of Wideband signals using Sub-Nyquist Samples

Direction of Arrival Estimation of Wideband Signals using Su...

引用

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

作者： Chaturvedi, Amal Fan, H. Howard Univ Cincinnati Dept Elect Engn & Comp Syst Cincinnati OH 45220 USA

ISBN: (纸本)9781479914814

This work is dedicated towards finding the Direction of Arrival (DOA) of Wideband signals using Sub-Nyquist samples. In a sensor array, the time delay between two sensors depends on the position of sources and thus its estimate could be used in finding the DOA of the sources. In this paper, we propose to estimate the time delay among sensors using cross-correlation of the signals received at the sensor array. The wider the bandwidth of the signal, the sharper will be the peak of its autocorrelation. Thus, it would be safe to assume that the autocorrelation of a wideband signal is sparse. The number of sharp peaks in the autocorrelation will be the same as the number of uncorrelated sources. The strength of Compressive Sampling (CS) lies in solving an underdetermined problem with a very high probability, provided the solution is sparse. This fits our wideband DOA problem very well, and is used to estimate the autocorrelation and hence the DOA of the signals with sub-Nyquist sampling. Simulations are given to support this concept.

关键词： broadband signal Direction of arrival estimation Autocorrelation signals United States Department of Agriculture time delay sensors broadband sensor arrays Cross correlation

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Microphone array speech enhancement by Bayesian estimation of spectral amplitude and phase

Microphone array speech enhancement by Bayesian estimation o...

引用

2nd ieee sensor array and multichannel signal processing workshop

作者： Balan, R Rosca, J Siemens Corp Res Multimedia & Video Technol Dept Princeton NJ 08540 USA

ISBN: (纸本)0780375513

Microphone arrays provide new opportunities for noise reduction and speech enhancement. This paper presents a novel decomposition of the estimation problems for short-time spectral amplitude (STSA), log STSA, and phase in the Bayesian estimation framework. The decomposition is based on the notion of sufficient statistics for the microphone array case. It nicely generalizes the well-known single-channel Ephraim-Malah estimators [4, 5] to the microphone array case. We also compare noise reduction obtained in the single channel with the two- and four-channel cases on real data.

关键词： Speech enhancement

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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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Dictionary Based Reconstruction and Classification of Randomly Sampled sensor Network Data

Dictionary Based Reconstruction and Classification of Random...

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

作者： Tsagkatakis, Grigorios Tsakalides, Panagiotis Fdn Res & Technol Hellas FORTH Inst Comp Sci Iraklion Greece

ISBN: (纸本)9781467310710

In this paper, we propose a method for recovering and classifying WSN data while minimizing the number of samples that need to be acquired, processed, and transmitted. The problem is formulated according to the recently proposed framework of Matrix Completion (MC), which asserts that a low rank matrix can be recovered from a small number of randomly sampled entries. The application of MC in WSN data is motivated by the assumption that sensory data exhibit intra-sensor correlations and that these data can be represented using known examples. We formulate the problem as that of recovering the low rank measurement matrix by encoding the contributions of known examples, the dictionary elements, for reconstructing and classifying the data. Experimental results using artificial data suggest that the proposed scheme is able to accurately reconstruct and classify the sensory data from a small number of measurements.

关键词： sensor networks

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Hierarchical Particle Filtering for Target Tracking in Multi-Modal sensor Networks

Hierarchical Particle Filtering for Target Tracking in Multi...

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

作者： Chavali, Phani Nehorai, Arye Washington Univ Preston M Green Dept Elect & Syst Engn St Louis MO 63130 USA

ISBN: (纸本)9781467310710

We propose a filtering method, called hierarchical particle filtering, for multi-modal sensor networks in which the unknown state vector is observed, through the measurements, in a hierarchical fashion. We partition the state space and the measurement space into lower dimensional subspaces. At each stage, we find an estimate of one partition using the measurements from the corresponding partition, and the information from the previous stages. We use hierarchical particle filtering for joint initiation, termination and tracking of multiple targets using multi-modal measurements. Numerical simulations demonstrate that the proposed filtering method accurately identifies the number and the categories of targets, and produces a lower mean-squared error (MSE) compared to the MSE obtained using a standard particle filter.

关键词： Particle filters metric space Target tracking Hierarchical sensor networks state space

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Non-Coherent Source Localization with Distributed sensor array Networks 12

Non-Coherent Source Localization with Distributed Sensor Arr...

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ieee 12th sensor array and multichannel signal processing workshop (SAM)

作者： Wan, Zhengyu Liu, Wei Willett, Peter Univ Sheffield Dept Elect & Elect Engn Sheffield S Yorkshire England Univ Connecticut Dept Elect & Comp Engn Storrs CT USA

ISBN: (纸本)9781665406338

The non-coherent source localization problem based on distributed sensor arrays can be formulated into a group sparsity based phase retrieval problem where only the magnitude (absolute value) of the received signals is available. Under such a framework, a two-dimensional localization method is proposed. Unlike traditional source localization methods, random phase errors at sensors of the distributed array will not affect estimation results by the proposed method. Simulation results indicate that the proposed non-coherent source localization method outperforms the traditional one in the presence of large phase errors, while still maintains an acceptable accuracy in the absence of phase errors.

关键词： Target localization distributed sensor array magnitude-only measurements group sparsity non-coherent detection

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Energy Detection for Decision Fusion in Wireless sensor Networks over Ricean-Mixture Fading

Energy Detection for Decision Fusion in Wireless Sensor Netw...

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

作者： Salvo Rossi, Pierluigi Ciuonzo, Domenico Ekman, Torbjoern Kansanen, Kimmo Univ Naples 2 Dept Ind & Informat Engn Naples Italy Norwegian Univ Sci & Technol Dept Elect & Telecommun Trondheim Norway

ISBN: (纸本)9781479914814

In this paper we focus on the energy detector for decision fusion in wireless sensor networks over multiple access channels. More specifically, we derive analytical performance in terms of global probability of false alarm and detection (including asymptotic performance for large number of sensors) when the fading is a Ricean mixture, i.e. channel coefficients are sampled from a Gaussian mixture (GM) distribution. The motivation for the GM is the ability to model real-world scenarios while keeping mathematical tractability. Analytical results are confirmed through numerical simulations.

关键词： Wireless sensor networks energy detector fading color Channel Coefficient probability of false alarm Fusion reactions Fusion, biological FUSION fusion (melting) Multiple Access Channel

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Sine-based EB-ESPRIT for source localization 10

Sine-based EB-ESPRIT for source localization

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

作者： Jo, Byeongho Choi, Jung-Woo Korea Adv Inst Sci & Technol Sch Elect Engn Daejeon South Korea

ISBN: (纸本)9781538647523

The eigenbeam-ESPRIT (EB-ESPRIT) is well known as a high-resolution parametric direction-of-arrival (DOA) estimation technique for a spherical microphone array. Unlike other eigenbeam beamformers such as EB-MVDR and EB-MUSIC, there is no need for exhaustive grid-search with EB-ESPRIT. However, when sources are positioned near the equator, the EB-ESPRIT inevitably induces a singularity problem due to the singularity of its tangent function utilized as a directional parameter. Here, a new EB-ESPRIT technique based on a nonsingular directional parameter is proposed. The proposed technique is derived from two sine-based recurrence relations, and hence, can fundamentally avoid the singularity problems and identify more sources than the conventional EB-ESPRIT.

关键词： recurrence relation spherical microphone array EB-ESPRIT singularity

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Airborne very long baseline interferometry and geolocation

Airborne very long baseline interferometry and geolocation

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4th ieee sensor array and multichannel signal processing workshop

作者： Carlsen, Eric C. Kolanek, James C. Sharpin, David L. Spectral Syst Inc 2611 Commons Blvd Beavercreek OH 45431 USA Signal Proc Special Goleta CA 93117 USA ATK Dayton OH 45420 USA

ISBN: (纸本)1424403081

A method is presented of performing geolocation of fixed emitters from a single, airborne platform using a two-element, very long baseline interferometer (VLBI) from 10 to 100 feet in length. The interferometer baseline is precisely tracked through a differential GPS system using auxiliary antennas placed in close proximity to the VLBI pair. A lever arm correction is applied to arrive at the VLBI baseline from the GPS measurements. A batch least squares processing algorithm is presented that operates on the interferometric phase measurements directly and resolves the associated ambiguities through global search strategies. A method of eliminating receiver phase bias by performing a difference operation is shown. Simulation results and Cramer-Rao lower bounds are also presented.

关键词： emitter location radio interferometry least squares methods radar position measurement radar signal processing

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An Efficient Optimization Framework for Learning General Signed Graphs from Smooth signals 13

An Efficient Optimization Framework for Learning General Sig...

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13rd ieee sensor array and multichannel signal processing workshop (SAM)

作者： Fong, Shi-Yuk So, Anthony Man-Cho Chinese Univ Hong Kong Dept Comp Sci & Engn Hong Kong Peoples R China Chinese Univ Hong Kong Dept Syst Engn & Engn Management Hong Kong Peoples R China

ISBN: (纸本)9798350344820;9798350344813

Graph learning has been widely used in many fields to study the relationships between different entities in a dataset. We present an optimization framework based on the proximal alternating direction method of multipliers (pADMM) for learning general signed graphs from smooth signals. We show that our proposed pADMM enjoys global convergence and a local linear convergence rate. Then, we demonstrate the effectiveness of the proposed framework through numerical experiments on signed graphs. Our proposed framework provides a promising approach for learning general signed graphs from smooth signals and can be a valuable tool for data analysis and decision-making in various fields.

关键词： Signed graph graph learning optimization graph signal processing proximal ADMM time-varying graphs

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