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Analysis of Prior-Subspace Estimation Schemes

Analysis of Prior-Subspace Estimation Schemes

引用

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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The array Geometry Design in Airborne Microwave 2-D Direction Finding

The Array Geometry Design in Airborne Microwave 2-D Directio...

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sensor array and multichannel signal processing workshop

作者： Cheol-Sun Park Won Jang Dae-Young Kim EW Laboratory Agency for Defence Development South Korea Department of Information & Communication Engineering Chungnam National University South Korea

ISBN: (纸本)1424403081

The resolving ambiguity of phase interferometer is necessary when the baseline separation between elements exceeds half wavelength since the phase difference between elements can only be measured modulo 2pi. It is difficult to meet the condition the minimum distance between two antennas is less than half wavelength for avoiding ambiguity in wideband operation. In this paper, we propose a simple and efficient array design method which minimizes the probability of ambiguity. This method adapts NLA (nonuniform linear array) geometry. And there is no need to maintain the distance between antennas less than half wavelength. We also show some numerical examples and experimental results of the 2-D array prototype for airborne application

关键词： Microwave antenna arrays Broadband antennas Antenna measurements Phase measurement Wavelength measurement Design methodology Adaptive arrays Linear antenna arrays Information geometry Prototypes

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Optical array Aspects of Computed Spectroscopy

Optical Array Aspects of Computed Spectroscopy

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sensor array and multichannel signal processing workshop

作者： R.T. Hoctor F.W. Wheeler E.B. Barrett GE Global Research Niskayuna NY USA ATC Lockheed Martin Space Systems Sunnyvale CA USA

Computed spectroscopytrade (CS) is a new approach to hyperspectral imaging recently introduced by the authors (R.T. Hoctor et al., 2006). The CS technique uses an adjustable optical array, which can be considered to be a form of delay-and-sum passive beamformer. Adopting this point of view, such an array can be analyzed using the (difference) coarray (R.T. Hoctor and S.A. Kassam, 1990), and a previous publication by the present authors (R.T. Hoctor et al., 2006) features a brief coarray-based analysis. In the present paper we review the computed spectroscopy method, give a coarray-based analysis of the approach, show how numerical problems arise in the reconstruction of wavenumber spectra at low spatial frequencies and give a method for addressing these problems in the computation. Additionally, we discuss an improved approach to discretization of the image formation model

关键词： Optical arrays Optical computing Spectroscopy Hyperspectral imaging Optical sensors Image reconstruction Optical imaging Frequency conversion Optical interferometry Satellites

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Performance Analysis of Linear Predictive Super-Resolution processing for Antenna arrays

Performance Analysis of Linear Predictive Super-Resolution P...

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sensor array and multichannel signal processing workshop

作者： Honglei Chen D. Kasilingam Department of Electrical & Computer Engineering University of Massachusetts Dartmouth North Dartmouth MA USA

Many applications in array processing require a high resolution beamforming method. For example, spatial division multiple access (SDMA) has been proposed to achieve higher system capacity in wireless systems. Implicit in SDMA is the ability to adaptively generate narrow antenna beam patterns, which ensures the physical separation between users and minimizes multiple user interference. However, antenna theory requires large antenna apertures to generate narrow beam patterns. This paper discusses an adaptive algorithm for extrapolating measurements from a small antenna array to a much larger virtual array. The technique utilizes linear prediction (LP) methods to perform the extrapolation. A least mean square (LMS) based algorithm was used to estimate the LP coefficients. Since the algorithm is linear, it serves both as a direction-of-arrival (DoA) estimator and a matched filter for retrieving the transmitted signal. Other popular high-resolution algorithms such as MUSIC are inherently nonlinear and thus cannot be used on their own for retrieving signal information. The performance of this algorithm is studied with respect to interference suppression, noise and spatial resolution. It is shown that the HR filter representing the LP process has poles corresponding to the DoA of the signal. The resulting LP coefficients can eliminate the interference between signals from different transmitters. However, no improvement in noise performance is seen because the receiver noise couples into the extrapolation process when two transmitters are closely located. The extrapolation algorithm is compared with the LCMV algorithm and found to produce similar results

关键词： Linear antenna arrays Performance analysis Adaptive arrays Spatial resolution Extrapolation array signal processing Multiaccess communication Aperture antennas Antenna theory Antenna arrays

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Planar Spherical Diffraction-arrays: Linear Sound Localization Algorithms

Planar Spherical Diffraction-Arrays: Linear Sound Localizati...

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sensor array and multichannel signal processing workshop

作者： A.A. Handzel Watertown MA USA

Sound source localization systems typically measure differences in time-of-arrival between microphones in free field arrays. Using a different concept, we previously designed and built a localization system that mimics nature's solution of harnessing wave diffraction about the head while relying only on two sensors positioned antipodally. Departing from the biological constraint of two sensors, I recently showed that for broadband sources, a high acuity array could be designed with merely three microphones. Yet adding more microphones may further increase acuity and robustness. The localization algorithm we have developed uses pair-wise comparisons between microphones, the number of which increases quadratically with the number of microphones, N. In order to minimize calculations in time sensitive applications, choosing a subset of pairs may be important. I examine this issue here through simulations of a hexagonal array. Thanks to the redundancy of spatial information contained in multiple microphone measurements, algorithms that are linear in N allow high acuity localization of broadband sources

关键词： Acoustic diffraction Microphone arrays sensor arrays Acoustic sensors Frequency Biosensors sensor systems Robustness Ear Information security

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A Probabilistic Graphical Model for Microphone array Source Separation using Rich Pre-Trained Source Models

A Probabilistic Graphical Model for Microphone Array Source ...

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sensor array and multichannel signal processing workshop

作者： H.T. Attias Golden Metallic Inc. San Francisco CA USA

Voice based computing applications, such as phone communication and speech recognition, use microphone arrays to capture voice from a human speaker. In many environments of interest, however, sounds from other sources interfere with the speaker's voice, posing severe problems for subsequent processing. This paper describes a new framework for treating this problem, and presents and demonstrates a new algorithm for the cancellation of interfering sounds. Our framework combines techniques from statistical machine learning with ideas from speech and audio processing. An important feature involves training rich probabilistic models on data from different types of relevant sound sources. Those source models are then incorporated into a larger probabilistic model of the observed microphone data. Using that model we derive our algorithm, which is of the expectation-maximization type and infers from data the clean sound of separate individual sources. We report very good results on data recorded in different environments

关键词： Microphone arrays Graphical models Source separation Loudspeakers Machine learning algorithms Computer applications Speech recognition Humans Machine learning Speech processing

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