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Blind Timing Synchronization for OFDM Systems via Adaptive Beamforming

Blind Timing Synchronization for OFDM Systems via Adaptive B...

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sensor array and multichannel signal processing workshop

作者： Kehu Yang Xueyao He E. E. Research Institute Xidian University Xi'an China

It is known that blind timing synchronization of OFDM systems can be realized for AWGN channels using the redundant information of cyclic prefix. In this paper, we extend the blind method to the case of array receivers via adaptive beamforming, and a new approach is proposed to improve the synchronization accuracy for high data rate OFDM systems, where rich multipath rays are present. The extended method is to coherently combine the desired signals of array receivers and suppress the undesired signals using adaptive beamforming. And the approach is to reduce the effect of multipath rays on synchronization. Simulation results show that in rich multipath scenarios the approach works effectively both in the absence and the presence of carrier frequency offset

关键词： Timing OFDM Adaptive systems array signal processing Frequency synchronization Adaptive arrays Baseband Helium Laboratories AWGN channels

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A hierarchical Bayesian approach to direction finding and beamforming

A hierarchical Bayesian approach to direction finding and be...

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sensor array and multichannel signal processing workshop

作者： S. Sirianunpiboon S.D. Howard J. Asenstorfer Defence Science and Technology Organisation Edinburgh Australia

It is well known in array processing that general multiple signal model based approaches for direction of arrival estimation, such as maximum likelihood (ML) or maximum a posteriori (MAP) estimation, are optimal. The major drawbacks of these approaches, is that not only do we need to know the number of signals a priori, but these methods also involve multivariate nonlinear maximizations which can often lead to an unacceptably large computational overhead. In this paper we propose a hierarchical Bayesian analysis for high accuracy direction finding and the resolution of closely spaced signals. The approach is to use a one signal model posterior distribution to obtain an initial coarse location of the signals. We then take each peak found and analyze it locally with a two signal model. In this way the computational load is kept modest as the optimizations are carried out only locally around the peak and there is no need to know, a priori, the number of signals. It is shown that this approach also provides a basis for the development of robust beamformers through the use of Laplace asymptotic expansions.

关键词： Bayesian methods array signal processing signal analysis Direction of arrival estimation Maximum likelihood estimation signal resolution sensor arrays Robustness Gaussian distribution Australia

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Maximum Likelihood Localization using GARCH Noise Models

Maximum Likelihood Localization using GARCH Noise Models

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sensor array and multichannel signal processing workshop

作者： H. Amiri H. Amindavar R.L. Kirlin Department of Electrical Engineering Amirkabir University of Technology슠 Tehran Iran Department of Electrical Engineering University of Victoria Victoria Canada

In this paper we propose a new source localization method using additive noise modeling based on generalized autoregressive conditional heteroscedasticity (GARCH) time-series. We use the GARCH noise model in the maximum likelihood (ML) sense for the estimation of direction of arrival (DOA) of impinging narrowband sources. In an actual application, the measurement of additive noise in a natural environment shows that noise can sometimes be significantly non-Gaussian and non-stationary. GARCH time-series are feasible for heavy-tail probability density function (PDF) and time-varying variances of stochastic noise process. We examine the suitability of the proposed method using simulated and experimental data

关键词： Additive noise sensor arrays Working environment noise Maximum likelihood estimation Direction of arrival estimation signal processing Narrowband Noise measurement signal processing algorithms Gaussian distribution

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Performance Analysis of ML Estimation under Misspecified Numbers of signals

Performance Analysis of ML Estimation under Misspecified Num...

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sensor array and multichannel signal processing workshop

作者： Pei-Jung Chung Institute for Digital Communications Joint Research Institute for Signal & Image Processing School of Engineering and Electronics University of Edinburgh UK

ISBN: (纸本)1424403081

The maximum likelihood (ML) approach for estimating direction of arrival (DOA) plays an important role in array processing. Its consistency and efficiency have been well established in literature. A common assumption is that the number of signals is known. In many applications, this information is not available and needs to be estimated. However, the estimated number of signals may not equal the true number of signals. Therefore, it is important to know whether the ML estimator provides any relevant information about the true parameters. In a previous study, the ML estimator was shown to converge to a well defined vector whose components coincide with the true parameters. In this work, we investigate the impact of model mismatch on estimation accuracy. Applying the theory of misspecified nonlinear regression models, we derive a compact formula for the asymptotic covariance matrix. Our analysis and simulation show that the variance increases when the number of signals is incorrectly chosen

关键词： Performance analysis Maximum likelihood estimation Direction of arrival estimation Covariance matrix signal processing array signal processing Digital communication Image processing Analysis of variance signal analysis

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Structured Covariance Estimation: Theory, Application, and Recent Results

Structured Covariance Estimation: Theory, Application, and R...

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sensor array and multichannel signal processing workshop

作者： D.R. Fuhrmann Electronic Systems and Signals Research Laboratory Department of Electrical and Systems Engineering Washington University of Saint Louis Saint Louis MO USA

The maximum-likelihood approach to structured covariance estimation and spectrum estimation has wide applicability in time series analysis, spectroscopy, adaptive beamforming and detection, remote sensing, radio astronomy, and radar imaging. Standard structured covariance EM algorithm with full model matrices is computationally demanding. Computational requirements drastically reduced when model matrices are sparse. Sparse structure may be achieved through appropriately chosen data preprocessing. We are investigating application in problem of airborne radar imaging from multiple viewpoints, previously computationally unrealistic

关键词： Estimation theory Covariance matrix Sparse matrices Maximum likelihood detection Maximum likelihood estimation Spectral analysis Image analysis Time series analysis Spectroscopy array signal processing

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Throughput of Large Wireless Networks on Square, Hexagonal and Triangular Grids

Throughput of Large Wireless Networks on Square, Hexagonal a...

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sensor array and multichannel signal processing workshop

作者： Kezhu Hong Yingbo Hua Department of Electrical Engineering University of California Riverside CA USA

Capacity analysis of sensor networks or wireless ad hoc networks has attracted a great attention in the past years. But the research in this area has primarily focused on scaling laws of arbitrary or random network instead of the exact capacity of given topologies. While the insight into how the capacity of an arbitrary or random network scales with the number of nodes in a given area is important, the exact capacity of a network depends on the network topology and can be more desirable in practice. In this paper, we compare the throughput of a large network with three possible topologies: square (rectangular), hexagonal and triangular. With a given topology, the network throughput also depends on the choice of routing protocols. We follow a synchronous array method (SAM) that is known so far to yield the highest throughout of a network on a rectangular grid

关键词： Throughput Wireless networks Network topology Mobile ad hoc networks Access protocols signal to noise ratio Capacitive sensors Wireless sensor networks Wireless mesh networks Routing protocols

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Programmable Processor Design for Givens Rotations based Applications

Programmable Processor Design for Givens Rotations based App...

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sensor array and multichannel signal processing workshop

作者： K. Dickson Z. Liu J.V. McCanny The Institute of Electronics Communications and Information Technology ECIT Queen''s University Belfast UK

A wide range of applications involve matrix decompositions which can be computed using givens rotations. A programmable processor for givens rotations offers more flexibility than highly tailored systolic array hardware implementations. The programmable processor design presented in this paper employs an approximate rotations method to compute givens rotations. Instantiations of this programmable processor can then be arranged/configured (i.e. in arrays of varying size and dimension) according to the requirements of the target application. Another advantage of this approach is that the processor can be programmed to compute different algorithms (e.g. QR decomposition, singular-value decomposition or a combination of both)

关键词： Process design Systolic arrays Matrix decomposition Hardware array signal processing MIMO Radar antennas Adaptive arrays Maximum likelihood detection Computer architecture

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Large Phased array Radar using Networked Small Parabolic Reflectors

Large Phased Array Radar using Networked Small Parabolic Ref...

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sensor array and multichannel signal processing workshop

作者： F. Amoozegar Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

Multifunction phased array systems with radar, telecom, and imaging applications have already been established for flat plate phased arrays of dipoles, or waveguides. In this paper the design trades and candidate options for combining the radar and telecom functions of the deep space network (DSN) into a single large transmit array of small parabolic reflectors will be discussed. In particular the effect of combing the radar and telecom functions on the sizes of individual antenna apertures and the corresponding spacing between the antenna elements of the array will be analyzed. A heterogeneous architecture for the DSN large transmit array is proposed to meet the radar and telecom requirements while considering the budget, scheduling, and strategic planning constrains

关键词： Phased arrays Radar antennas Telecommunications Antenna arrays Radar imaging Aperture antennas Dipole antennas Solar system Calibration Propulsion

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Direction-Finding Results for a Vector sensor Antenna on a Small UAV

Direction-Finding Results for a Vector Sensor Antenna on a S...

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sensor array and multichannel signal processing workshop

作者： S. Appadwedula C.M. Keller MIT Lincoln Laboratories Lexington MA USA

On small platforms, angle-of-arrival (AOA) estimation of an E-M signal can be accomplished with colocated antennas measuring multiple components of the propagating wave. An electrically small vector sensor (VS) antenna constructed above and below the wing of a small UAV measures three components of the propagating wave. Determining the AOA involves fitting known "calibration" AOAs and corresponding antenna response to a modeled response. The least-squares calibration approach described here determines the azimuth and elevation AOAs for sources located at typical elevation angles to within a few degrees, agreeing with the Cramer-Rao lower bound (CRLB). These results justify the use of small VS antennas to do direction finding (DF) in high SNR environments

关键词： Navigation Directive antennas Unmanned aerial vehicles Antenna measurements Calibration Antennas and propagation Antenna accessories Dipole antennas Azimuth Electric variables measurement

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MUSIC using Off-Origin Hessians of the Second Characteristic Function

MUSIC using Off-Origin Hessians of the Second Characteristic...

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sensor array and multichannel signal processing workshop

作者： A. Yeredor School of Electrical Engineering Tel-Aviv University Tel-Aviv Israel

In its classical form, the multiple signal classification (MUSIC) algorithm applies eigen-decomposition to the estimated correlation matrix of the noisy sensors' outputs in order to estimate the directions of arrival (DOAs) of several sources. When the noise is spatially white, consistent estimates of the DOAs are obtained. However, when the noise is spatially correlated (and / or has different variances at different sensors), the correlation-based MUSIC cannot produce consistent DOA estimates, unless the noise covariance is known in advance. To mitigate this drawback, the use of certain matrices of higher order statistics (HOS), mainly fourth-order cumulants, has been proposed, which can still lead to consistent DOA estimates when the noise is not spatially white, as long as it has a Gaussian distribution. However, estimates of the required HOS often introduce larger variances; Moreover, if the sources happen to have null cumulants of the chosen order, they remain unaccounted for in the algorithm. In this paper we propose a new target-matrix to substitute HOS as the input to MUSIC. Our target matrix is based on subtracting the observations' correlation matrix from Hessians of their second characteristic function, evaluated at several "processing points". These Hessians are related to the array steering-vectors (hence to the DOAs) in the same way as the correlation matrix, and can be easily estimated from the data. The subtraction of the correlation matrices eliminates (asymptotically) the effect of any additive independent Gaussian noise, hence maintaining consistency. We demonstrate the attainable improvement in comparative simulation

关键词： Multiple signal classification Direction of arrival estimation Matrices Gaussian noise Classification algorithms sensor phenomena and characterization White noise Covariance matrix Higher order statistics Gaussian distribution

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