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A novel augmented complex valued kernel LMS

A novel augmented complex valued kernel LMS

引用

sensor array and multichannel signal processing workshop

作者： Felipe A. Tobar Anthony Kuh Danilo P. Mandic Department of Electrical and Electronic Engineering Imperial College London UK Department of Electrical Engineering University of Hawaii USA

A novel class of complex valued kernel least mean square (CKLMS) algorithms is introduced with the aim to provide physical meaning to the mapping between the primal and dual space termed the independent CKLMS (iCKLMS). the general class of CKLMS algorithms is also extended in the widely linear sense to develop online kernel algorithms suitable for the processing of general complex valued signals, both circular and noncircular. the so-introduced augmented complex kernel least mean square (ACKLMS) algorithms are verified on adaptive prediction of nonlinear and nonstationary complex wind signals.

关键词： Kernel Heuristic algorithms Least squares approximation Prediction algorithms signal processing algorithms Wind forecasting Wind speed

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Amplify-and-forward compressed sensing as a PHY-layer secrecy solution in wireless sensor networks

Amplify-and-forward compressed sensing as a PHY-layer secrec...

引用

sensor array and multichannel signal processing workshop

作者： J.E. Barceló-Lladó Antoni Morell Gonzalo Seco-Granados Dpt. Telecom. and Syst. Engineering Universitat Autònoma Barcelona Bellaterra Barcelona Spain

Results in distributed compressed sensing show that this technique can be applied to wireless sensor networks in order to reduce the power consumption and the amount of channel uses. In this paper we extend such results with the study of the physical layer secrecy performance. In particular, we focus on an amplify-and-forward compressed sensing scheme (AF-CS) for the case when malicious eavesdropping nodes are listening. We demonstrate that this scheme achieves perfect secrecy in presence of one eavesdropper (and also for a small number of them). We also show that a very high number of eavesdropping nodes are required to perfectly recover the signal in comparison to other distributed compressed sensing schemes in the literature.

关键词： Wireless sensor networks sensors Compressed sensing Physical layer Channel estimation Relays Vectors

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Detection of DVB-T2 control symbols in passive radar systems

Detection of DVB-T2 control symbols in passive radar systems

引用

sensor array and multichannel signal processing workshop

作者： Keijo Pölönen Visa Koivunen SMARAD CoE Department of Signal Processing and Acoustics Aalto University School of Electrical Engineering Aalto Finland

Passive radars offer several advantages over the conventional radar systems by using a source of illumination that is independent from the receivers and primarily used in other purposes. the second generation digital television standard DVB-T2 is a good alternative to be utilized as an illuminating system. Passive radar receivers should be able to detect the target echo at very low signal-to-noise ratios. In this paper, a novel detection method for the DVB-T2 signal is proposed that fulfills these conditions. Distributions of test statistic are established and the performance of the method is verified with simulations. It is shown that the proposed method is suitable for passive radar systems and can be used without the exact knowledge of the transmitted signal waveform.

关键词： Digital video broadcasting signal to noise ratio Passive radar Receivers OFDM Vectors

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Beamformer design for nonstationary signals by means of interfrequency correlations

Beamformer design for nonstationary signals by means of inte...

引用

sensor array and multichannel signal processing workshop

作者： Tofigh Naghibi Beat Pfister Speech Processing Group Computer Engineering and Networks Laboratory ETH Zurich Switzerland

the wide-sense stationary assumption has been frequently employed in array processing, since it results in uncorrelated frequency bins and consequently major simplifications arise. However, unlike stationary signals, significant interfrequency correlations are observable in nonstationary signals like speech. Here, we drop the stationarity assumption and will show that taking interfrequency correlations into account leads to higher noise reduction. We develop a framework to design nonstationary beamformers similar to the stationary Frost beamformers. Based on the noise model, it can be used to design both fixed and adaptive beamformers. the nonstationary beamformer derived here is a set of time-varying filters and hence can be seen as a set of time-frequency or wavelet transform filters.

关键词： arrays Noise Covariance matrix Correlation Microphones Vectors Power generation

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A distributed algorithm for two-way multiple-relay networks

A distributed algorithm for two-way multiple-relay networks

引用

sensor array and multichannel signal processing workshop

作者： C. Lameiro J. Vía I. Santamaria Communications Engineering Department (DICOM) University of Cantabria Santander Spain

In this paper we propose an efficient transmission strategy for the two-way relay channel (TWRC) with multiple relays, when these are multiple-input multiple-output (MIMO) transceivers that apply the amplify-and-forward (AF) protocol. Although the optimal beamforming strategy is known, it requires a central node, with channel state information (CSI) of the entire network, to compute all the beamforming matrices, which is impractical. To reduce the overhead, in this paper we present a distributed algorithm for the computation of the relay beamforming matrices. the proposed algorithm divides the problem in two stages. First, each relay computes its own beamforming matrix in parallel using only local CSI. Next, a distributed beamforming is applied to make the signals add up coherently at the nodes. Although the proposed algorithm is suboptimal, we show through simulations that it performs very close to the optimal achievable rate region.

关键词： Relays array signal processing MIMO Protocols signal processing algorithms signal to noise ratio Upper bound

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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...

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sensor array and multichannel signal processing workshop

作者： Oscar Martinez-Graullera David Romero-Laorden Alberto Ibañez Luis G. Ullate CAEND (UPM-CSIC) Madrid Spain

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 60λ. 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° in lateral resolution.

关键词： arrays Dispersion Apertures Coherence Dynamic range Spirals Image resolution

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Limited field-of-view multimodal sensor adaptation for data association

Limited field-of-view multimodal sensor adaptation for data ...

引用

sensor array and multichannel signal processing workshop

作者： Sean M. O'Rourke A. Lee Swindlehurst Center for Pervasive Communications and Computing University of California Irvine Irvine CA USA

We have investigated the utility of field-of-view adaptation for multimodal sensing in cluttered multi-target environments. Measurement data from multiple integrated sensors are collected at a fusion center, which employs a soft association procedure to integrate them into the estimation procedure. A variance penalty model for the limited fields-of-view property is incorporated into the state estimation procedure. this model also forms the basis of an optimization problem that determines the best next-step sensing parameters for the changing target environment. Numerical simulations demonstrate the benefit of the proposed method for both tracking and association metrics compared to a non-adaptive tracker.

关键词： sensors Target tracking Clutter Radio frequency Noise measurement Noise Vectors

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Covariance estimation in time varying ARMA processes

Covariance estimation in time varying ARMA processes

引用

sensor array and multichannel signal processing workshop

作者： Ami Wiesel Amir Globerson Hebrew University of Jerusalem Israel

We consider large scale covariance estimation using a small number of samples in applications where there is a natural ordering between the random variables. the two classical approaches to this problem rely on banded covariance and banded inverse covariance structures, corresponding to time varying moving average (MA) and autoregressive (AR) models, respectively. Motivated by this analogy to spectral estimation and the well known modeling power of autoregressive moving average (ARMA) processes, we propose a novel time varying ARMA covariance structure. Similarly to known results in the context of AR and MA, we address the completion of an ARMA covariance matrix from its main band, and its estimation based on random samples. Finally, we examine the advantages of our proposed methods using numerical experiments.

关键词： Covariance matrix Estimation Autoregressive processes Vectors Mathematical model signal processing Equations

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An L1-norm linearly constrained LMS algorithm applied to adaptive beamforming

An L1-norm linearly constrained LMS algorithm applied to ada...

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sensor array and multichannel signal processing workshop

作者： José F. de Andrade Marcello L. R. de Campos José A. Apolinário Program of Electrical Engineering (PEE)-COPPE Federal University of Rio de Janeiro Rio de Janeiro Brazil Department of Electrical Engineering (SE/3) Military Institute of Engineering Rio de Janeiro Brazil

We propose in this work an L 1 -norm Linearly-Constrained Least-Mean-Square (L 1 -CLMS) algorithm. In addition to the linear constraints present in the CLMS algorithm, the L 1 -CLMS algorithm takes into account an L 1 -norm penalty on the filter coefficients. the performance of the L 1 -CLMS algorithm is evaluated for a time-varying system identification under Gaussian noise and for an adaptive beamforming scenario. the effectiveness of the L 1 -CLMS algorithm is demonstrated by comparing, via computer simulations, its results with the CLMS algorithm. When employed in a sensor array, the L 1 -norm constraint increases the convergence rate making the proposed algorithm a good candidate for adaptive beamforming applications.

关键词： signal processing algorithms arrays Convergence array signal processing Heuristic algorithms Azimuth Vectors

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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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sensor array and multichannel signal processing workshop

作者： Phani Chavali Arye Nehorai Preston M. Green Department of Electrical and Systems Engineering Washington University in St. Louis Saint Louis MO USA

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： Target tracking Vectors Atmospheric measurements Particle measurements Cameras Multimodal sensors Standards

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