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Real-Time Implementation of a Distributed Voice Activity Detector

Real-Time Implementation of a Distributed Voice Activity Det...

引用

sensor array and multichannel signal processing workshop

作者： V. Berisha Homin Kwon A. Spanias Department of Electrical Engineering Arizona State University Tempe AZ USA

Wireless sensor networks have been applied successfully in real-time distributed and collaborative sensing. In these situations, each sensor is responsible for extracting pertinent information from the surrounding environment and transmitting it to other sensors and/or to the main processing station. This is done while operating under several constraints, such as low computational capabilities, limited arithmetic precision, and the need to conserve power. In this paper, we present a low-complexity voice activity detector and a gender classifier for implementation on the Crossbow sensor motes. In addition, a decision fusion algorithm that resides at the base station is also implemented. A series of experiments that characterize the performance of the algorithms under varying conditions and in different environments are presented and several of the challenges we faced in developing this real-time implementation are discussed

关键词： Detectors Wireless sensor networks Acoustic sensors Collaboration sensor phenomena and characterization Base stations Data mining Arithmetic Hardware Noise level

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Joint Source and Relay Optimization for a Non-Regenerative MIMO Relay

Joint Source and Relay Optimization for a Non-Regenerative M...

引用

sensor array and multichannel signal processing workshop

作者： Zheng Fang Yingbo Hua J.C. Koshy Department of Electrical Engineering University of California Riverside CA USA Advanced Wireless Signal Processing Research Telcordia Technologies Inc. Red Bank NJ USA

We consider a non-regenerative MIMO relay system where the source, relay and destination are all equipped with multiple antennas. The relay does not decode the packets but performs a multi-dimensional amplify-and-forward function (a relay matrix) on the baseband signals. Under the condition that the source is white, the relay matrix that maximizes the capacity between the source and the destination has been previously found. In this paper, we show a new result on how the source covariance matrix and the relay matrix can be jointly optimized to maximize the source-destination capacity. It is shown that the optimal coordinate system governed by the previously discovered relay matrix is still valid under the joint optimization, and the joint optimization yields a further capacity gain when the SNR at the relay is low

关键词： Relays MIMO Covariance matrix Power system relaying Decoding Baseband Government Multidimensional signal processing Springs Multidimensional systems

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Analysis of Prior-Subspace Estimation Schemes

Analysis of Prior-Subspace Estimation Schemes

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sensor array and multichannel signal processing workshop

作者： G. Bouleux R. Boyer Laboratoire des Signaux et Système (LSS) CNRS-Université Paris-Sud France

In the context of the direction-of-arrival (DOA) estimation problem, we can sometimes assume that we have a priori knowledge of a subset of the DOA for several sources. In that situation, some works have proposed to tacking into account of this knowledge to improve the localization of the unknown sources. The key idea is based on an orthogonal deflation of the signal subspace. In a companion paper, we have derived and analyzed the CRB associated to this model and we have shown that the prior-knowledge of a subset of the DOA is beneficial only for coherent or highly correlated sources associated to closely-spaced DOA. In particular, for uncorrelated sources with closely-spaced DOA, the orthogonal deflation cannot help the estimation of the unknown DOA. Finally, we suggest that a possible solution could be to use oblique projectors. In this paper, we follow this line and we propose two algorithms based on the MinNorm principle

关键词： Direction of arrival estimation sensor arrays Narrowband Maximum likelihood estimation Multiple signal classification Uninterruptible power systems Radar Computational efficiency MIMO

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Unitary Cyclic MUSIC for Direction Finding in GPS Receivers

Unitary Cyclic MUSIC for Direction Finding in GPS Receivers

引用

sensor array and multichannel signal processing workshop

作者： M. Sahmoudi M.G. Amin Wireless Communications and Positioning Lab Center for Advanced Communications Villanova University Villanova PA USA

Several anti-jam techniques for GPS receivers rely on the direction-of-arrival (DOA) of the satellite signals. These angles change with moving GPS receiver platforms and, as such, they should be constantly estimated for the purpose of jammer nulling and beamforming. In this paper, we propose a new approach for directional finding for multi-antenna GPS receivers. This approach is based on a new unitary-cyclic subspace method, which utilizes the modulation and repetition properties of the GPS code to discriminate against jammer signals. We apply the forward-backward spatial smoothing technique to the cyclic array covariance matrix to decorrelate the direct path from multipath, so nulling of the undesired signals can occur. A unitary formulation is considered for real-valued eigendecomposition which aims at reducing the payload in the GPS receivers. Simulations are provided showing that the proposed approach has better performance than existing high-resolution methods that neither apply cyclostationary or unitary transformations for DOA estimation

关键词： Multiple signal classification Global Positioning System Direction of arrival estimation Jamming Satellites array signal processing Modulation coding Smoothing methods Covariance matrix Decorrelation

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Optimal Adaptive array and Angle Tracking for Multiple Targets - A Re-examination of Optimal array processing

Optimal Adaptive Array and Angle Tracking for Multiple Targe...

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sensor array and multichannel signal processing workshop

作者： Huaijin Gu Louisiana Tech University USA

ISBN: (纸本)1424403081

The optimal array for detecting the signal from a desired direction but contaminated by receiver noise and strong interference from different sources with unknown arriving-angles is re-examined. The well-known optimal array is obtained by inverting the covariance matrix of interference and noise to maximize the signal to interference and noise ratio (SINR). In practice, the covariance matrix is unknown and has to be estimated by a sample covariance matrix. The optimal array is thus estimated by inverting the sample covariance matrix. This procedure has been employed in optimal array research without challenge. However, it is shown in this paper that the estimated optimal array fails to yield the highest SINR in the case of unknown arriving-angles. Instead the highest SINR can be achieved by optimally estimating the arriving-angles of interference followed by a constrained matched filter, which maximizes the signal to noise ratio subject to canceling the interference from the estimated arriving-angles. In order to reduce the computational burden, an angle-tracking system for multiple targets is adopted to achieve the optimal estimation of arriving-angles. The resulting system of angle-tracking adaptive array offers the highest SINR at a computational burden only on 2 the order of N middot M 2 multiplications within a radar range-cellDeltatau, rather than N 3 multiplications in the well-known but questionable estimated optimal array. Here N is the number of sensors in the array and M the number of interference sources. Typically, N = 1,000 in a planar radar array, M = 2-10 and Deltatau = 1 mus. Numerical simulations confirm the theoretical results

关键词： Adaptive arrays Target tracking array signal processing signal to noise ratio Interference Covariance matrix sensor arrays Radar tracking signal detection Yield estimation

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On Proposal Functions for Cost-Reference Particle Filtering

On Proposal Functions for Cost-Reference Particle Filtering

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sensor array and multichannel signal processing workshop

作者： M.F. Bugallo M. Vemula P.M. Djuric Department of Electrical and Computer Engineering Stony Brook University Stony Brook NY USA

Standard particle filtering (SPF) schemes rely on the availability of probability distributions of the state and observation noises involved in the dynamic state space model. Cost reference particle filtering (CRPF) techniques have proven to be a viable and robust alternative in situations when the probability distributions of these noise processes are unknown. In this paper, we propose two new CRPF methods which use different proposal functions from the one of the original CRPF method. The proposed algorithms are applied to target tracking in a wireless sensor network. The performance of the proposed methods is demonstrated by computer simulations

关键词： Proposals Filtering Probability distribution Costs State-space methods Wireless sensor networks Computer simulation Decision support systems Noise measurement Time measurement

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Performance tradeoffs among beamforming approaches

Performance tradeoffs among beamforming approaches

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sensor array and multichannel signal processing workshop

作者： Yue Rong Y.C. Eldar A.B. Gershman University of California Riverside Riverside CA USA Technion-Israel Institute of Technology Haifa Israel Darmstadt University of Technology Darmstadt Germany

In this paper, three main criteria for the adaptive beamformer design are discussed: maximal signal-to-interference-plus-noise ratio (MSINR), minimal mean-squared error (MMSE), and minimal least-square error (MLSE). Although in the case of exactly known power and steering vector of the signal-of-interest (SOI), there are beamformers that can simultaneously meet the MMSE and MSINR criteria, this is no longer true when the exact knowledge of the steering vector is unavailable. To account for steering vector errors, a meaningful approach is to model the actual steering vector as random. In this paper, it is shown that in the latter case, the MMSE and MSINR criteria can not be simultaneously attained. We study the achievable region in the MSE-SINR plane and propose a new adaptive beamformer that can attain a frontier of operating points on the boundary of this region and, therefore, provide an optimal performance tradeoff among the MSINR and MMSE criteria. It is also shown that in the random steering vector case, the MLSE and MSINR criteria are simultaneously achievable and a new adaptive beamformer is proposed that satisfies both these criteria.

关键词： array signal processing signal to noise ratio Maximum likelihood estimation signal design Radar applications Sonar applications Digital communication Amplitude estimation Phase estimation Phase detection

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Analysis of the Directivity Gain of a Synthetic Aperture in Active and Passive Modes

Analysis of the Directivity Gain of a Synthetic Aperture in ...

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sensor array and multichannel signal processing workshop

作者： D. Billon Thales Underwater Systems Brest France

While synthetic aperture sonar is now a mature technology for active imaging of the sea floor, its use for improving passive detection or localisation of underwater acoustic sources is still a research issue. In the first part, we show that the phase shifts for passive synthetic aperture beamforming do not depend on the steering direction. Hence a passive synthetic aperture has the same directivity pattern like the real aperture that it originates from. The directivity gain of an active synthetic aperture is caused by the phase origin reset at each transmit time resulting in a phase discontinuity depending on the bearing angle. Model-based array processing (MBAP), which estimates a source state from the array vector signal, has been proposed as an alternative to passive synthetic aperture for improving source localization. In the second part, we propose a MBAP approach based on a hidden Markov model (HMM) where the signal phase is a third order polynomial. Numerical simulation shows that it does not improve the bearing angle accuracy with respect to an HMM tracker performing on the square magnitude output of real aperture beamforming. This result is in accordance with the fact that both estimators meet the same Cramer-Rao lower bound. But the new method has interesting detection potential

关键词： Hidden Markov models array signal processing Synthetic aperture sonar Acoustic imaging Sea floor Acoustic signal detection Sonar detection Underwater tracking Underwater acoustics State estimation

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A Multisource Calibration Method for Phased array Radio Telescopes

A Multisource Calibration Method for Phased Array Radio Tele...

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sensor array and multichannel signal processing workshop

作者： S.J. Wijnholds A. Boonstra ASTRON Dwingeloo Netherlands

For low frequency observations (< 300 MHz) the radio astronomical community is currently developing a number of new instruments such as the low frequency array (LOFAR), the Mileura wide field array (MWA) and the primeval structure telescope (PaST). These telescopes require new calibration algorithms since phased arrays require an all-sky approach to imaging and calibration. This implies that the calibration will generally have to deal with a multitude of sources. In this paper we will discuss a multisource calibration method to estimate the gains and phases of the receiving elements without having to solve for the receiver noise powers at the same time. Our method is able to handle arbitrary known source models. We will show that the proposed algorithm is asymptotically efficient by comparing the results from Monte Carlo simulations with the Cramer-Rao bound for the underlying data model

关键词： Phased arrays Calibration Radio astronomy Matrix converters Frequency Telescopes Instruments Data models Phase estimation Low-frequency noise

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Advanced Optical Processor for Arbitrary Waveform Radar Imaging

Advanced Optical Processor for Arbitrary Waveform Radar Imag...

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sensor array and multichannel signal processing workshop

作者： K. Frampton J. Lafuse J. Aloi M. Brown Essex Corporation Columbia MD USA

Essex has developed a prototype hybrid optical/digital processor for range-Doppler image formation using wideband arbitrary waveforms. The processor is called the advanced optical processor (AOP) and is a hybrid acousto-optic/digital processor that generates high dynamic range, range-Doppler images from wideband radar returns in real time. The AOP was first tested at a U.S. Government facility in November 2005. The AOP is currently scheduled to be tested with a range radar in April 2006. The laboratory testing included three waveform types and verification of all the necessary trigger control signals. The range radar testing will include collection and processing of the same three waveform signals to demonstrate arbitrary waveform capability. The AOP supports high resolution processing necessary for target discrimination and kill assessment by enabling the use of true arbitrary wideband waveforms. The selected architecture combines the advantages of both optical signal processing for the front-end receiver and high-speed digital signal processing for the real-time processing. Its size is a 6U form-factor and fits within the 6U electronic chassis

关键词： Laser radar Radar imaging Optical receivers Optical signal processing High speed optical techniques Acoustic testing Wideband Prototypes Hybrid power systems Dynamic range

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