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检索条件"任意字段=2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016"

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Data orthogonalization in sensor array signal processing

Data orthogonalization in sensor array signal processing

引用

2nd ieee sensor array and multichannel signal processing workshop

作者： Owsley, NL Off Naval Res Arlington VA 22217 USA

ISBN: (纸本)0780375513

In this primarily tutorial paper, a perspective on the development of Adaptive Data Orthogonalization (ADO) for spatial sensor array sampled data vectors is presented. The development of ADO methods is traced from a generalization of the split array, cross-correlation arrival angle tracker for a single source, plane wave arrival to multiple coherent arrivals. Development is followed through to the more recent maximization of the ratio of two quadratic forms that expresses beamformer array gain. Specifically, the reduced complexity implementation of a signal model error robust Minimum Variance Distortionless Response (MVDR) Adaptive Beamformer (ABF) is described. This robust beamformer is a simple, explicit linear blend (combination) of the inherently robust shaded time delay-and-sum Conventional Beamformer (CBF) and the Enhanced Minimum Variance (EMV) Dominant Mode Rejection (DMR) ABF. This ABF construction places an easily implemented upper bound on the signal suppression caused by signal model mismatch and allows a trade-off between spatial resolution and Main Lobe signal Maintenance (MLM). Several methods for robust DMR ABF are compared.

关键词： array processing

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Numerically-robust adaptive subspace tracking using householder transformations

Numerically-robust adaptive subspace tracking using househol...

引用

1st ieee sensor array and multichannel signal processing workshop (sam 2000)

作者： Douglas, SC So Methodist Univ Dept Elect Engn Dallas TX 75275 USA

ISBN: (纸本)0780363396

In this paper, we develop simple principal and minor subspace tracking algorithms that exactly maintain the orthonormality of the subspace matrix estimate over time. Each of these algorithms use m identical Householder transformations to update the rows of the subspace matrix estimate at each time instant. Unlike many other approaches, ours have asymptotic complexities that scale linearly with the number of adaptive coefficients. We show that existing gradient-based and projection approximation subspace tracking (PAST) methods are first-order approximate versions of our proposed methods, and we also derive several more-accurate approximations. Simulations verify the excellent numerical behaviors of the proposed methods in subspace tracking tasks.

关键词： Algorithm design and analysis Approximation algorithms array signal processing Data mining Data visualization Pattern recognition signal processing

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COMPRESSED SENSING OF GAUSS-MARKOV RANDOM FIELDS WITH WIRELESS sensor NETWORKS

COMPRESSED SENSING OF GAUSS-MARKOV RANDOM FIELDS WITH WIRELE...

引用

ieee sensor array and multichannel signal processing workshop

作者： Oka, Anand Lampe, Lutz Univ British Columbia Dept Elect & Comp Engn Vancouver BC V5Z 1M9 Canada

ISBN: (纸本)9781424422401

We propose a scalable and energy efficient method for reconstructing a 'sparse' Gauss-Markov random field that is observed by an array of sensors and described over wireless channels to a fusion center. The encoder is universal, i.e. invariant to the statistical model of the source and the channel, and is based on compressed sensing. The reconstruction algorithms exploit the a-priori statistical information about the field and the channel at the fusion center to yield a performance comparable to information theoretic bounds. Furthermore, by putting stringent constraints on the sensing matrix we avoid (or even eliminate) inter-sensor communication while suffering negligible degradation in performance.

关键词： Compressed sensing

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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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Ambiguity Function-Based ESPRIT Algorithm for FDA-MIMO Radar Target Localization 11

Ambiguity Function-Based ESPRIT Algorithm for FDA-MIMO Radar...

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ieee 11th sensor array and multichannel signal processing workshop (sam)

作者： Xu, Ziting Huang, Bang Hu, Huawei Chen, Hui Wang, Wen-Qin Univ Elect Sci & Technol China Sch Informat & Commun Chengdu Peoples R China

ISBN: (纸本)9781728119465

Frequency-diverse array (FDA) can provide a range-angle-time dependent beamforming capability that could make a difference in some radar applications. However, the joint range-angle estimation of FDA will inevitably increase the complexity due to the coupling range and angle response. Estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm cannot be used directly to estimate the angle and range because it does not meet the rotation invariance criterion. In this paper, an ambiguity function (AF)-based method is proposed to avoid the coupling range and angle problem for the FDA and multiple-input multiple-output (MIMO) combined radar to realize high-resolution range and angle estimation. Numerical results show its advantages over conventional method.

关键词： Ambiguity function ESPRIT frequency diverse array (FDA) Localization multiple-input multiple-output (MIMO)

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Distributed Posterior Cramer-Rao Lower Bound for Nonlinear Sequential Bayesian Estimation

Distributed Posterior Cramer-Rao Lower Bound for Nonlinear S...

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

作者： Mohammadi, Arash Asif, Amir York Univ Toronto ON M3J 1P3 Canada

ISBN: (纸本)9781467310710

In distributed sensor networks, the posterior Cramer-Rao lower bound (PCRLB) has recently been used [1] as a selection criteria for sensor management decisions, where new sensor nodes are deployed or existing ones reactivated to optimize the network's performance. Previous algorithms to compute the PCRLB are derived for the centralized [2] and hierarchical architectures [3] using a fusion centre that makes them inappropriate for distributed sensor management. Only recently a suboptimal expression [1] for the distributed architecture has been proposed, which can at times lead to large errors especially in systems with highly non-linear dynamics. The paper derives the optimal PCRLB for the distributed architecture. In other words, we derive a recursive procedure to determine the overall Fisher information matrix (FIM), i.e., the inverse of the PCRLB, from local FIMs of the distributed estimators. The proposed distributed PCRLB is independent of the filtering mechanism used and closely follows its centralized counterpart.

关键词： Bayesian Estimation Distributed signal processing Particle Filters Posterior Cramer Rao Lower Bounds

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Distributed Multiarray Noise Reduction With Online Estimation Of Masks And Spatial Filters 11

Distributed Multiarray Noise Reduction With Online Estimatio...

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ieee 11th sensor array and multichannel signal processing workshop (sam)

作者： Bartolewska, Julitta Kowalczyk, Konrad AGH Univ Sci & Technol Dept Elect PL-30059 Krakow Poland

ISBN: (纸本)9781728119465

A rapid increase in popularity of smart devices equipped with acoustic sensors enables the design of speech enhancement methods for distributed setups. In this work, we present a distributed noise reduction scheme in which the time-frequency masks and spatial filters are estimated at the nodes based on the locally available microphone signals and the compressed signals received from other nodes, where each node transmits only a single signal. The proposed block processing facilitates online estimation of masks and distributed spatial filters in an interchanged fashion. The results of performed numerical experiments indicate that the proposed online distributed noise reduction scheme performs similarly to the centralized approach, in which signals of all microphones of the distributed arrays are available for joint processing, and it significantly outperforms the local approach in which only the local microphone signals are available for the estimation of masks and spatial filters.

关键词： distributed sensor arrays mask-based noise reduction distributed spatial filtering multichannel Wiener filter

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Listener-Position Adaptive Crosstalk Cancelation Using A Parameterized Superdirective Beamformer 10

Listener-Position Adaptive Crosstalk Cancelation Using A Par...

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

作者： Ma, Xiaohui Hohnerlein, Christoph Ahrens, Jens Dynaudio AS DK-8660 Skanderborg Denmark Berlin Inst Technol Ernst Reuter Pl 7 D-10587 Berlin Germany Chalmers Univ Technol S-41296 Gothenburg Sweden Aarhus Univ Dept Engn Finlandsgade 22 DK-8200 Aarhus N Denmark

ISBN: (纸本)9781538647523

We present a method for cancelation of the acoustic crosstalk between the ears of a listener using a linear loudspeaker array. This allows for controlling the signals that arise at listener's ear independently of each other so that binaural cues can be imposed. We employ superdirective near-field beamforming (SDB) over the vast part of the frequency range. Allowing the listener to move in front of the array requires the computation of a new SDB solution for each possible position of the listener, which is a computationally expensive procedure. We show that the beamformer weights exhibit a very smooth evolution for listening positions along a line parallel to the array. This makes it straightforward to parameterize pre-computed beamformer weights with a few parameters for each frequency. Upon realtime execution, the beamformer weights can be determined efficiently for any arbitrary position along the listener contour from the parameters with negligible error. Simulation results show that the proposed beamformer provides a higher channel separation than previously published solutions while maintaining robustness.

关键词： Loudspeakers Ear Crosstalk array signal processing Robustness sensor arrays"

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Tracking Multiple Evolving Threats With Cluttered Surveillance Observations 10

Tracking Multiple Evolving Threats With Cluttered Surveillan...

引用

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

作者： Sutton, Zachariah Willett, Peter Bar-Shalom, Yaakov Univ Connecticut Dept ECE Storrs CT 06269 USA

ISBN: (纸本)9781538647523

Many threats in the form of human actions (terrorist attacks, military actions, etc.) can be stochastically modeled by someone with relevant expert knowledge. In this work, a threat is taken to be a sequence of actions that evolve over time and culminate at some ultimate goal. A model would be a hypothesis as to how a threat would develop, and what kind of observable evidence it would produce along the way. This modeling method allows us to attempt detection using the preliminary evidence of a threat. This would theoretically allow the user to take preemptive action;i.e. the user can interfere with the threat before its culmination. This work presents a method of stochastically modeling these types of processes using Hidden Markov Models (HMMs). We then present a detection scheme based on random finite set (RFS) filters (Bernoulli filters) that allows for detection of multiple threat processes using a single cluttered stream of observed data.

关键词： Hidden Markov models Clutter Radio frequency Markov processes array signal processing sensor arrays"

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sample complexity trade-offs for synthetic aperture based high-resolution estimation and detection 11

Sample complexity trade-offs for synthetic aperture based hi...

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ieee 11th sensor array and multichannel signal processing workshop (sam)

作者： Qiao, Heng Sarangi, Pulak Alnumay, Yazeed Pal, Piya Univ Calif San Diego Dept Elect & Comp Engn San Diego CA 92103 USA

ISBN: (纸本)9781728119465

This paper critically examines the potential performance benefits offered by motion of sparse arrays for direction-of-arrival (DOA) estimation. The motivation behind utilizing array motion is to increase the number of consecutive difference lags. However, creating a synthetic array also requires more temporal measurements compared to the static (non-synthetic) array. For the first time, we rigorously analyze the trade-off between the required number of temporal samples and the length of the difference co-array to understand when synthetic arrays offer distinct advantages. As a concrete result, we show that if the ratio of the number of consecutive lags of the difference coarray of sparse arrays with and without motion is above a universal threshold, the synthetic array outperforms its non-synthetic counterpart and has a smaller estimation error. Our claims are demonstrated both theoretically and through numerical experiments(1).

关键词： Sparse array Difference Co-array array Motion Synthetic array sample Complexity Trade-Off

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