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sensor array and multichannel signal processing workshop

作者： Dinh-Quy Nguyen Xuexin Yap Woon-Seng Gan Yong-Kim Chong Digital Signal Processing Laboratory Nanyang Technological University Singapore

Recently, a time reversal operator method that is applied to ultrasonic detection and focusing with arrays of transducers has been proposed. This method is known as the DORT (Decomposition de lpsilaOperateur de Retournement Temporel). The DORT method requires the measurement of the inter-element impulse responses of the propagating medium for all pairs of elements in the array. Time reversal operator (TRO) is deduced from these responses and diagonalized. The eigenvector and eigenvalue of TRO is analyzed to perform selective focusing on different scatterers. We develop the numerical technique of DORT method by using the Greenpsilas function estimation in homogeneous and multiple scattering medium. This technique can set up the feasibility study of DORT method to perform selective focusing on multiple scatterers.

关键词： Focusing Eigenvalues and eigenfunctions Scattering Transducers Numerical models Media Acoustics

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Localization in sensor networks - A matrix regression approach

Localization in sensor networks - A matrix regression approa...

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sensor array and multichannel signal processing workshop

作者： Paul Honeine Cedric Richard Mehdi Essoloh Hichem Snoussi Institut Charles Delaunay (FRE CNRS 2848)-LM2S Université de technologie de Troyes Troyes France

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.

关键词： Distance measurement Kernel Optimization Distributed algorithms Wireless sensor networks Network topology Topology

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Canonical decomposition of even higher order cumulant arrays for blind underdetermined mixture identification

Canonical decomposition of even higher order cumulant arrays...

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sensor array and multichannel signal processing workshop

作者： Ahmad Karfoul Laurent Albera Lieven De Lathauwer INSERM U642 Rennes France Leuven Subfaculty Science and Technology Katholieke Universiteit Leuven Kortrijk Belgium

A new family of methods, named 2q-ORBIT (q > 1), is proposed in this paper in order to blindly identify potentially underdetermined mixtures of statistically independent sources. These methods are based on the canonical decomposition of q-th order (q ges 2) cumulants. The latter decomposition is brought back to the decomposition of a third order array whose one loading matrix is unitary. Such a decomposition is then computed by alterning and repeating two schemes until convergence: the first one consists in solving a Procrustes problem while the second one needs to compute the best rank-1 approximation of several q-th order arrays. Computer results show a good efficiency of the proposed methods with respect to classical cumulant-based algorithms especially in the underdetermined case.

关键词： Matrix decomposition sensors signal to noise ratio sensor arrays signal processing algorithms Equations Convergence

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Hybrid interference suppression for multistatic radar

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IET RADAR SONAR AND NAVIGATION 2008年第5期2卷 323-333页

作者： Blunt, S. D. Dower, W. Gerlach, K. Univ Kansas ITTC Radar Syst Lab Lawrence KS 66045 USA USN Res Lab Div Radar Washington DC 20375 USA

The accurate estimation of a monostatic radar range pro. le is considered when in the presence of multistatic radar interference for which the illuminating waveforms are assumed known. In an effort to approach the ideal interference-free performance, the range-domain 'beamforming' properties of the recently developed multistatic adaptive pulse compression ( MAPC) algorithm is herein combined with the well-known CLEAN algorithm which operates on an interference-subtraction basis. Two versions of this hybridised methodology are presented and compared. To ascertain relative sensitivity, both the mean-squared error and the probability of detection are examined as a function of SNR when in the presence of multistatic interference. It is demonstrated that the respective merits of MAPC and CLEAN can be used to offset the limitations of the other and thereby combine to provide significant additional sensitivity improvement.

关键词： Radar theory Electromagnetic compatibility and interference CLEAN algorithm hybrid interference suppression probability multistatic radar Other topics in statistics Radar equipment, systems and applications MAPC algorithm range-domain-beamforming property mean-squared error monostatic radar radar interference mean square error methods array signal processing multistatic adaptive pulse compression Interpolation and function approximation (numerical analysis) pulse compression adaptive radar interference suppression

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Blind detection of exclusive source activity periods in reverberant acoustic environments

Blind detection of exclusive source activity periods in reve...

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sensor array and multichannel signal processing workshop

作者： Robert M. Nickel Department of Electrical Engineering Bucknell University Lewisburg PA USA

Blind separation and dereverberation of acoustic sources is still considered a very challenging task despite many years of research and the availability of increasingly powerful computation engines. The complexity of the task can be significantly reduced for sources that exhibit sufficiently long exclusive activity periods (EAPs). EAPs are time intervals during which only one source is active and all other sources are inactive (i.e. zero). During EAPs the estimation of the underlying system parameters simplifies from a MIMO type to a SIMO type. The existence of EAPs is not guaranteed for arbitrary signal classes. EAPs occur very frequently, however, in recordings of conversational speech. In this paper we propose a new low complexity method for EAP detection which significantly outperforms earlier approaches.

关键词： Speech Mathematical model Equations Speech processing Acoustics Nickel Transfer functions

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

MULTIVARIATE SPECTRAL RECONSTRUCTION OF STAP COVARIANCE MATR...

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2008 ieee sensor array and multichannel signal processing workshop

作者： Yuri I. Abramovich Ben A. Johnson Nicholas K. Spencer ISR Division DSTO Australia Edinburgh Australia ITR-University of South Australia SA Australia Adelaide Research & Innovation Pty Ltd (ARI) DSTO Australia Edinburgh SA Australia

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 Space-time adaptive processing

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MAP-PF 3D position tracking using multiple sensor array

MAP-PF 3D position tracking using multiple sensor array

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sensor array and multichannel signal processing workshop

作者： Kristine L. Bell Richard Pitre Department of Statistics George Mason University Fairfax VA USA RobTre Research Limited Liability Company Clarksville MD USA

The maximum a posteriori penalty function (MAP-PF) approach is applied to three-dimensional (3D) target position tracking of multiple wideband sources using multiple distributed sensor arrays. The track estimation problem is formulated directly from the array data using the maximum a posteriori (MAP) estimation criterion. The penalty function (PF) method of nonlinear programming is used to obtain a tractable solution. A sequential update procedure is developed in which penalized maximum likelihood estimates of target directions-of-arrival (DOAs) and spectra are computed at each array and then used as synthetic measurements in a set of extended Kalman filters. The two steps are coupled via the penalty function. The current target states are used to guide the DOA/spectrum estimation, and the estimated signal spectra control the influence of the DOA estimates from each array on the final track estimates. The algorithm can be implemented in a decentralized manner where DOA/spectrum estimation is performed at the arrays, and track estimation is performed at a central processing site.

关键词： Target tracking Direction of arrival estimation arrays Estimation Spectral analysis Maximum likelihood estimation sensor arrays

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On the Cramér-Rao bound for the constrained and unconstrained complex parameters

On the Cramér-Rao bound for the constrained and unconstrain...

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sensor array and multichannel signal processing workshop

作者： Esa Ollila Visa Koivunen Jan Eriksson Department of Mathematical Sciences University of Oulu Oulu Finland Signal Processing Laboratory Helsinki University of Technology Finland

We derive a complex form of the unconstrained and constrained Cramer-Rao lower bound (CRB) of composite real parameters formed by stacking the real and imaginary part of the complex parameters. The derived complex constrained and unconstrained CRB is easy to calculate and possesses similar structure as in the real parameter case but with the real covariance, Jacobian and the Fisher information matrix replaced by complex matrices with analogous interpretations. The advantage of the complex CRB is that it is oftentimes easier to calculate than its real form. It is highlighted that a statistic that attains a bound on the complex covariance matrix alone do not necessarily attain the CRB since complex covariance matrix does not provide a full second-order description of a complex statistic since also the pseudo-covariance matrix is needed. Our derivations also lead to some new insights and theory that are similar to real CRB theory.

关键词： Covariance matrix Jacobian matrices Symmetric matrices Matrices signal processing Estimation Cramer-Rao bounds

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Robust adaptive beamformers: A beampattern shaping approach

Robust adaptive beamformers: A beampattern shaping approach

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sensor array and multichannel signal processing workshop

作者： S. E. Nai W. Ser Z. L. Yu School of Electrical and Electronic Engineering Signal Processing Nanyang Technological University Singapore

Adaptive beamformers can degrade drastically in practice because they are highly sensitive to mismatches between the exploited assumptions and the actual characteristics of the sensor array, environment and sources. At low snapshots, the sidelobes can get very high due to errors in the array covariance matrix. This degrades the signal-to-interference-plus-noise-ratio (SINR). Recently, a robust adaptive beamformer based on worst-case optimization (RAB-WC), has reformulated beamforming as a second-order cone programming (SOCP) problem. It exhibits adaptive interference-rejection capability and robustness against large steering direction errors. However, the sidelobes in RAB-WC are indirectly controlled by a regularization factor and it is not clear how the factor value should be selected. In this paper, we propose a new framework based on the use of a set of beampattern shaping constraints. With this framework, the beamformer possesses not only adaptive interference-rejection capability and robustness against large steering direction errors, but also direct sidelobe control simultaneously. Unlike other state-of-the-art robust adaptive beamformers, the proposed beamformer is robust against moving interferences too. The proposed framework is generic and many beamformers can be derived to tackle specific problems.

关键词： Interference Robustness arrays array signal processing signal to noise ratio Covariance matrix Chromium

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EVALUATION OF EMERGING FREQUENCY DOMAIN CONVOLUTIVE BLIND SOURCE SEPARATION ALGORITHMS BASED ON REAL ROOM RECORDINGS

EVALUATION OF EMERGING FREQUENCY DOMAIN CONVOLUTIVE BLIND SO...

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2008 ieee sensor array and multichannel signal processing workshop

作者： S. M. Naqvi Y. Zhang T. Tsalaile S. Sanei J. A. Chambers Department of Electronic Electrical Engineering Loughborough University Loughborough UK Centre of Digital Signal Processing Cardiff University Cardiff UK

This paper presents a comparative study of three of the emerging frequency domain convolutive blind source separation (FDCBSS) techniques i.e. convolutive blind separation of non-stationary sources due to Parra and Spence, penalty function-based joint diagonalization approach for convolutive blind separation of nonstationary sources due to Wang et al. and a geometrically constrained multimodal approach for convolutive blind source separation due to Sanei et al. Objective evaluation is performed on the basis of signal to interference ratio (SIR), performance index (PI) and solution to the permutation problem. The results confirm that a multimodal approach is necessary to properly mitigate the permutation in BSS and ultimately to solve the cocktail party problem. In other words, it is to make BSS semiblind by exploiting prior geometrical information, and thereby providing the framework to find robust solutions for more challenging source separation with moving speakers.

关键词： Frequency domain (BSS) Geometrical constraints Orthogonal/nonorthogonal constraints Penalty functions Cocktail party problem and multimodal signal separation

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