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2012 ieee 7th sensor array and multichannel signal processing workshop, SAM 2012

作者： Xia, S.Z. Dai, F.Z. Liu, H.W. National Lab. of Radar Signal Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781467310710

A heterogeneous Markov chain (MC) model, instead of the homogeneous MC model, is proposed in this paper to describe target existence variable for Bayesian track-before-detect. the proposed model is more consistent with the transitions of target existence variable, which leads to the improvement of the performance of detection and tracking. © 2012 ieee.

关键词： Markov processes

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DoA Estimation Performance of UCAs with Reduced Number of sensors using Phase-Mode Transformation and Small Sample Support 12

DoA Estimation Performance of UCAs with Reduced Number of Se...

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

作者： Liali, Guilherme Murmel Apolinario, Jose A., Jr. de Campos, Marcello L. R. Ramos, Antonio L. L. Mil Inst Engn Depts Def Engn Rio De Janeiro Brazil Mil Inst Engn Depts Elect Engn Rio De Janeiro Brazil Univ Fed Rio de Janeiro Elect Engn Rio De Janeiro Brazil Univ South Eastern Norway Dept Sci & Ind Syst Kongsberg Norway

ISBN: (纸本)9781665406338

In this work, we assess the performance of a Uniform Circular array featuring a reduced number of sensors and using small sample support comprised of only a few snapshots. We begin by analyzing the limitations of the phase-mode transformation in the context of a uniform circular array with a reduced number of sensors. Next, we address the challenging issue of having limited sample support, followed by a brief discussion of the techniques that can be used to mitigate the degradation caused by the two aforementioned problems. Several experiments are conducted to evaluate the DoA estimation performance of narrowband acoustic signals in different scenarios, having water as propagating media.

关键词： Direction of Arrival Estimation Uniform Circular array Phase-mode Transformation Small Sample Support

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Decision Fusion for Carbon Dioxide Release Detection from Pressure Relief Devices 12

Decision Fusion for Carbon Dioxide Release Detection from Pr...

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

作者： Tabella, Gianluca Di Martino, Yuri Ciuonzo, Domenico Paltrinieri, Nicola Wang, Xiaodong Rossi, Pierluigi Salvo Norwegian Univ Sci & Technol Dept Elect Syst Trondheim Norway Columbia Univ Dept Elect Engn New York NY 10027 USA Univ Naples Federico II Dept Elect Engn & Informat Technol DIETI Naples Italy Norwegian Univ Sci & Technol Dept Mech & Ind Engn Trondheim Norway SINTEF Energy Res Dept Gas Technol Trondheim Norway

ISBN: (纸本)9781665406338

this work investigates the distributed detection of carbon dioxide (CO2) release from storage tanks caused by the opening of pressure relief devices via inexpensive sensor devices in an industrial context. A realistic model of the dispersion is put forward in this paper. Both full-precision and rate-limited setups for sensors are considered, and fusion rules capitalizing the dispersion model are derived. Simulations analyze the performance trends with relevant system parameters.

关键词： Carbon Dioxide Decision Fusion Distributed Detection Industry 4.0 Internet of things Wireless sensor Networks

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Robust adaptive beamforming for general-rank signal models using worst-case performance optimization

Robust adaptive beamforming for general-rank signal models u...

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2nd ieee sensor array and multichannel signal processing workshop

作者： Shahbazpanahi, S Gershman, AB Luo, ZQ Wong, KM McMaster Univ Dept Elect & Comp Engn Commun Res Lab Hamilton ON L8S 4K1 Canada

ISBN: (纸本)0780375513

the performance of adaptive beamforming methods is known to degrade in the presence of even small mismatches between the actual and presumed array responses to the desired signal. In this paper, we propose a new powerful approach to robust adaptive beamforming in the presence of unknown arbitrary-type mismatches of the desired signal array response. Our approach is developed for the most general case of an arbitrary dimension of the desired signal subspace and is applicable to both rank-one and higher-rank desired signal models. the proposed beamformer is based on an explicit modeling of uncertainties in the desired signal array response and data covariance matrix as well as worst-case performance optimization. Simple closed-form solution to this robust adaptive beamforming problem is obtained. this solution naturally combines two different types of diagonal loading which are applied to the sample and presumed signal covariance matrices. Our new robust beamformer has a computational complexity comparable to that of the traditional adaptive beamforming algorithms while offers a greatly improved robustness and faster convergence rate as compared to existing robust beamformers.

关键词： Covariance matrix

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Decision fusion in MIMO wireless sensor networks with channel state information

Decision fusion in MIMO wireless sensor networks with channe...

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2012 ieee 7th sensor array and multichannel signal processing workshop, SAM 2012

作者： Ciuonzo, Domenico Romano, Gianmarco Salvo Rossi, Pierluigi Department of Information Engineering Second University of Naples Italy

ISBN: (纸本)9781467310710

We study channel-aware binary decision fusion over a Rayleigh flat fading shared channel with multiple antennas at the Decision Fusion Center (DFC). We derive the optimum and three sub-optimal fusion rules, namely the Max-Log, the Chair-Varshney - Maximum Likelihood and the Maximum Ratio Combining rules. Simulation results for the performance are presented in terms of Probability of Detection (under a fixed false alarm rate) vs SNR and number of antennas. the effect of multiple antennas at the DFC for the presented rules is analyzed, showing benefits and limitations of the choice. © 2012 ieee.

关键词： Maximum likelihood

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Direction of arrival estimation in sparse arrays in the presence of unknown colored block-correlated noise fields

Direction of arrival estimation in sparse arrays in the pres...

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2nd ieee sensor array and multichannel signal processing workshop

作者： Vorobyov, SA Gershman, AB Wong, KM McMaster Univ Dept Elect & Comp Engn Commun Res Lab Hamilton ON L8S 4K1 Canada

ISBN: (纸本)0780375513

We address the problem of maximum likelihood (ML) direction-of-arrival (DOA) estimation in unknown spatially correlated noise fields using sensor arrays composed of multiple subarrays on a sparse grid. In such arrays, the noise covariance matrix has the block-diagonal structure which enables to reduce substantially the number of nuisance noise parameters and ensure the identifiability of the underlying DOA estimation problem. A new deterministic ML DOA estimator is derived for the considered class of sparse sensor arrays. the proposed approach concentrates the estimation problem with respect to all nuisance parameters. In contrast to the analytic concentration used in the conventional ML techniques, the proposed estimator is based on an iterative procedure, which includes a stepwise concentration of the LL function. Our algorithm is free of any further structural constraints or parametric model restrictions which are usually imposed on the noise covariance matrix and received signals in most of existing ML-based approaches to DOA estimation in spatially correlated noise.

关键词： White noise

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Data-supported optimization for maximum likelihood DOA estimation

Data-supported optimization for maximum likelihood DOA estim...

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

作者： Gershman, AB Stoica, P McMaster Univ Dept Elect & Comp Engn Commun Res Lab Hamilton ON L8S 4K1 Canada

ISBN: (纸本)0780363396

We introduce a new conceptually simple and computationally effective solution to the maximum likelihood (ML) direction of arrival (DOA) estimation problem that consists of maximizing the likelihood function (LF) over a set of points derived from the data. Two different data-supported optimization (DSO) based techniques are formulated. which use the data-supported grid points obtained by means of ESPRIT-like and root-MUSIC-like methods, respectively. the first technique is shown to be the method of choice in the short sample size case, whereas the second technique is applicable to situations where the number of snapshots is large. We show that the data-supported grid search of the LF provides the performance similar to that achieved by the genetic algorithm (GA), but at a significantly lower computational cost.

关键词： Computational efficiency Control systems Councils Direction of arrival estimation Frequency estimation Genetic algorithms Information technology Maximum likelihood estimation Optimization methods signal processing algorithms

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A relationship between time-reversal imaging and maximum-likelihood scattering estimation

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ieee TRANSACTIONS ON signal processing 2007年第9期55卷 4707-4711页

作者： Shi, Gang Nehorai, Arye IEEE Division of Biostatistics Washington University School of Medicine Department of Electrical and Systems Engineering Washington University

Time-reversal methods have attracted increasing interest recently. the so-called computational time-reversal approach creates an image of the illuminated scene by computing the back-propagated field and is useful for detecting and estimating targets in the scene. In Shi and Nehorai ["Maximum Likelihood Estimation of Point Scatterers for Computational Time-Reversal Imaging," Communications in Information and Systems, vol. 5, no. 2, pp. 227-256, 20051], we estimated point scatterers by maximum-likelihood estimate (MLE) using the Born-approximated physical model, as well as the Foldy-Lax model. In this correspondence, we further find an explicit relationship between energy-based basic time-reversal imaging and the MLE approach: the time-reversal imaging function differs by only a scaling factor from the likelihood imaging function using the estimated scattering potential when a single-scatterer model is employed. Furthermore, this scaling factor is a function of the imaging position only. We show that, as a result, time-reversal imaging has a near-far problem that tends to produce a weaker image for areas further away from the imaging arrays, whereas the MLE-based image is more balanced. Experimental results confirm this conclusion.

关键词： maximum-likelihood estimate (MLE) multistatic near-far problem time-reversal imaging

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Approximate Maximum Likelihood DOA estimation in multiplicative noise environments

Approximate Maximum Likelihood DOA estimation in multiplicat...

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

作者： Besson, O Vincent, F Stoica, P Gershman, AB ENSICA Dept Avion & Syst Toulouse France

ISBN: (纸本)0780363396

We consider the problem of localizing a source by means of a uniform linear array of sensors when the received signal is corrupted by multiplicative noise. Since the exact Maximum Likelihood (ML) estimator is computationally intensive, two approximate solutions are proposed, originating from the analysis of the high and low signal to Noise Ratio (SNR) cases, respectively. First, starting with the no additive noise case, a very simple approximate ML (AML(1)) estimator is derived. A theoretical expression for its asymptotic variance in the presence of additive noise is derived. It shows that the AML1 estimator has a performance close to the Cramer-Rao bound (CRB) for moderate to high SNR. Next, the low SNR case is considered and the corresponding AML(2) solution is derived. It is shown that the approximate ML criterion can be concentrated with respect to (w.r.t.) both the multiplicative and additive noise powers, leaving out a 2-D minimization problem instead of a 4-D problem required by the exact ML. Numerical results illustrate the performance of the estimators and confirm the validity of the theoretical analysis.

关键词： Additive noise Direction of arrival estimation Integrated circuit modeling Integrated circuit noise Maximum likelihood estimation Parameter estimation Scattering sensor arrays signal to noise ratio Working environment noise

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Exploiting array Geometry for Reduced-Subspace Channel Estimation in RIS-Aided Communications 12

Exploiting Array Geometry for Reduced-Subspace Channel Estim...

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

作者： Demir, Ozlem Tugfe Bjornson, Emil Sanguinetti, Luca KTH Royal Inst Technol Dept Comp Sci Kista Sweden Univ Pisa Dipartimento Ingn Informaz Pisa Italy

ISBN: (纸本)9781665406338

A reconfigurable intelligent surface (RIS) can be used to improve the channel gain between a base station (BS) and user equipment (UE), but only if its N reflecting elements are configured properly. this requires accurate estimation of the cascaded channel from the UE to the BS through each RIS element. If the channel structure is not exploited, pilot sequences of length N must be used, which is a major practical challenge since N is typically at the order of hundreds. To address this problem without requiring user-specific channel statistics, we propose a novel estimator, called reduced-subspace least squares (RS-LS) estimator, that only uses knowledge of the array geometry. the RIS phase-shift pattern is optimized to minimize the mean-square error of the channel estimates. the RS-LS estimator largely outperforms the conventional leastsquares estimator, and can be utilized with a much shorter pilot length since it exploits the fact that the array geometry confines the possible channel realizations to a reduced-rank subspace.

关键词： RIS channel estimation reduced-subspace least squares reduced pilot length pilot design

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