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检索条件"任意字段=2008 IEEE Sensor Array and Multichannel Signal Processing Workshop"

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2012 ieee 7th sensor array and multichannel signal processing workshop, SAM 2012

2012 IEEE 7th Sensor Array and Multichannel Signal Processin...

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2012 ieee 7th sensor array and multichannel signal processing workshop, SAM 2012

ISBN: (纸本)9781467310710

The proceedings contain 134 papers. The topics discussed include: decentralized data processing and management in smart grid via gossiping;fast anomaly detection in smart grids via sparse approximation theory;widely linear state space models for frequency estimation in unbalanced three-phase systems;deadline scheduling for large scale charging of electric vehicles with renewable energy;change detection in smart grids using errors in variables models;analysis of a joint access and scheduling scheme for residential energy management controller;adaptive pulse design for space-time adaptive processing;untangling multipath returns in MIMO radar via waveform diversity;sparsity-based MIMO noise radar for multiple target estimation;a cognitive approach for ambiguity function shaping;direct Cartesian detection, localization, and de-ghosting for passive multistatic radar;and optimal precoding design for decentralized detection of deterministic signals.

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Deterministic blind identification in antenna array processing

Deterministic blind identification in antenna array processi...

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sensor array and multichannel signal processing workshop

作者： Souleymen Sahnoun Pierre Comon GIPSA-Lab CNRS UMR5216 France

The estimation of directions of arrival is formulated as the decomposition of a 3-way array into a sum of rank-one terms. However, a low-rank tensor approximation does not always exist. We propose an optimization technique based on differentiable angular constraints on the factors, ensuring the existence of the low-rank tensor decomposition. The efficiency of the proposed algorithm is demonstrated via numerical simulations, and compared to Cramér-Rao bounds.

关键词： arrays signal processing algorithms Estimation Direction-of-arrival estimation Tensile stress Vectors

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Multidimensional ESPRIT: A coupled canonical polyadic decomposition approach

Multidimensional ESPRIT: A coupled canonical polyadic decomp...

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sensor array and multichannel signal processing workshop

作者： Mikael Sørensen Lieven De Lathauwer Group Science KU Leuven Kulak Kortrijk Belgium

The ESPRIT method is a classical method for one-dimensional harmonic retrieval. During the past two decades it has become apparent that several applications in signal processing correspond to the less studied Multi-dimensional Harmonic Retrieval (MHR) problem. In order to accommodate this demand, we propose an extension of ESPRIT to MHR based on the coupled canonical polyadic decomposition. This leads to a dedicated uniqueness condition and an algebraic framework for MHR.

关键词： Tensile stress Harmonic analysis Vectors Generators Symmetric matrices signal processing algorithms

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Generalized coprime array configurations

Generalized coprime array configurations

引用

sensor array and multichannel signal processing workshop

作者： Si Qin Yimin D. Zhang Moeness G. Amin Center for Advanced Communications Villanova University Villanova PA USA

A coprime array consists of two uniform linear subarrays that construct an effective difference co-array with certain desirable characteristics. In this paper, we propose a generalized coprime array concept through the compression of the interelement spacing of one constituting subarray. As such, the existing variations of coprime array and nested array structures are represented as special cases. The achievable unique lags as well as consecutive lags in the resulting virtual array are analytically expressed, and the direction-of-arrival estimation performance is examined using both the MUSIC algorithm and sparse signal reconstruction techniques.

关键词： arrays Direction-of-arrival estimation Multiple signal classification Estimation Vectors Covariance matrices Conferences

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On the amount of training in coordinated massive MIMO systems

On the amount of training in coordinated massive MIMO system...

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sensor array and multichannel signal processing workshop

作者： David Neumann Andreas Gründinger Michael Joham Wolfgang Utschick Associate Institute for Signal Processing Technische Universitat Munchen Munich Germany

Coordinated training significantly reduces the impact of pilot contamination in massive MIMO systems. Moreover, coordinated systems can use additional training resources in an effective manner, making it worthwhile to spend more resources on training than the necessary minimum. For a fixed channel coherence time, we analyze the trade-off between spending resources on training or data symbols for the uncoordinated and the coordinated case.

关键词： Training Base stations Interference MIMO signal to noise ratio Antennas Approximation methods

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Preprocessing algorithm for source localisation in a multipath environment

Preprocessing algorithm for source localisation in a multipa...

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sensor array and multichannel signal processing workshop

作者： Evangelos Venieris Athanassios Manikas Department of Electrical and Electronic Engineering Imperial College London London UK

Several methods have been developed which allow the estimation of the location of an existing source with considerable accuracy in the absence of multipaths. However, if, in addition to the Line-of-Sight (LOS) path, non-LOS (NLOS) paths are also present, then all existing localisation algorithms dramatically fail to estimate the location of the source. In this paper, a passive array processing algorithm is proposed, which, if used prior to a localisation approach, suppresses all the multipath contributions in the received signal except for that of the LOS path. The performance of the proposed algorithm is evaluated through computer simulation studies.

关键词： arrays signal processing algorithms Vectors Equations Mathematical model Delays signal processing

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Application of Krylov based methods in calibration for radio astronomy

Application of Krylov based methods in calibration for radio...

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sensor array and multichannel signal processing workshop

作者： Ahmad Mouri Sardarabadi Alle-Jan van der Veen Delft University of Technology

As the number of antennas in the modern radio-telescopes increases, the computational complexity of the calibration algorithms becomes more and more important. In this paper we use the Khatri-Rao structure of the covariance data model used for such calibrations and combine it with Krylov subspace based methods to achieve accurate calibration results with low complexity, very small memory usage and fast convergence properties. We also demonstrate the proposed method on experimental data measured by the LOFAR radio-telescope.

关键词： arrays Calibration Vectors Covariance matrices Jacobian matrices Complexity theory signal processing

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Direction of arrival estimation of harmonic signal using single moving sensor

Direction of arrival estimation of harmonic signal using sin...

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sensor array and multichannel signal processing workshop

作者： Yusuke Hioka Masako Kishida Department of Electrical and Computer Engineering University of Canterbury Christchurch New Zealand

A signal processing algorithm for estimating the direction of arrival of a harmonic signal using only a single sensor is proposed. The method is based on the recently invented architecture called CAROUSEL, which makes use of the Doppler effect caused by observing signals using the sensor in a circular motion. The proposed method estimates the direction of arrival from the amount of phase shift of a harmonic component caused by the Doppler effect. Simulation using various harmonic signals including synthesised speech phonemes prove the proposed algorithm is able to accurately estimate the direction of arrival of the harmonic signals.

关键词： Direction-of-arrival estimation Harmonic analysis Estimation Frequency estimation arrays signal to noise ratio

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Interference mitigation in GNSS receivers by array signal processing: A software radio approach

Interference mitigation in GNSS receivers by array signal pr...

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sensor array and multichannel signal processing workshop

作者： Javier Arribas Pau Closas Carles Fernández-Prades Centre Tecnologic de Telecomunicacions de Catalunya (CTTC) Carl Friedrich Gauss Spain

The fact that most of high-accuracy positioning and distributed timing services, including safety-critical operations, rely on Global Navigation Satellite Systems (GNSS) has raised the concern of possible denial-of-service situations. Complementary to time- and frequency-domain mitigation techniques, it is well known that antenna-array based receivers can benefit from spatial domain processing and effectively mitigate unintentional and intentional Radio Frequency Interferences (RFIs). In this work, we propose a software-based GNSS receiver architecture that implements a real-time, array-based signal acquisition algorithm based on the Generalized Likelihood Ratio Test, combined with a null-steering spatial filter for signal tracking, showing its RFI rejection capabilities.

关键词： Global Positioning System arrays Receivers Interference Satellites signal processing algorithms Satellite broadcasting

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Regularized robust estimation of mean and covariance matrix under heavy tails and outliers

Regularized robust estimation of mean and covariance matrix ...

引用

sensor array and multichannel signal processing workshop

作者： Ying Sun Prabhu Babu Daniel P. Palomar Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

In this paper we consider the regularized mean and covariance estimation problem for samples drawn from elliptical family of distributions. The proposed estimator yields robust estimates when the underlying distribution is heavy-tailed or when there are outliers in the data samples. In the scenario that the number of samples is small, it shrinks the estimator of the mean and covariance towards arbitrary given prior targets. Numerical algorithms are designed for the estimator based on the majorization-minimization framework and the simulation shows that the proposed estimator achieves considerably better performance.

关键词： Robustness Covariance matrices signal processing algorithms Maximum likelihood estimation arrays signal processing

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