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共 931 条记录，以下是431-440 订阅

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Application of Krylov based methods in calibration for radio astronomy

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

引用

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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Random switch antenna array FMCW radar and its signal processing method

Random switch antenna array FMCW radar and its signal proces...

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sensor array and multichannel signal processing workshop

作者： Chenxi Hu Huadong Meng Wei Wang Gang Li Xiqin Wang Department of Electronic Engineering Tsinghua University Beijing China Xi'an Electronic Engineering Research Institute Xi'an China

ISBN: (纸本)9781467310703

In this paper, random switch antenna array (RSAA) is proposed to apply to the switch antenna array (SAA) frequency-modulated continuous-wave (FMCW) radar system. Firstly, the signal model and signal processing method of RSAA is analyzed and it shows that RSAA can successfully solve azimuth-velocity coupling problem. then we suppose a method by using RSAA to reduce the switching frequency and sampling rate based on sparse signal representation with multiple measurement vectors (MMV). It is shown in simulations that the proposed algorithms yield better performance in terms of azimuth-velocity decoupling and can obtain high image accuracy with less observation data.

关键词： Switches arrays Radar antennas Antenna arrays Azimuth Radar Multiplexing

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Incorporating array nonidealities into adaptive Capon beamformer for source tracking

Incorporating array nonidealities into adaptive Capon beamfo...

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sensor array and multichannel signal processing workshop

作者： Mário Costa Visa Koivunen Department of Signal Processing and Acoustics SMARAD CoE Aalto University Aalto Finland

An adaptive algorithm for azimuth-angle estimation of moving sources in the presence of array nonidealities is proposed. the method, termed unitary element-space Capon (UESCapon) beamformer, is robust in the face of small number of snapshots and fully takes into account effects such as mutual coupling, mounting platform reflections, and sensor's misplacement errors. Unlike most of the robust beamformers available in the literature, the proposed method is based on QR-decomposition and real-valued polynomial root tracking. Furthermore, it is applicable to sensor arrays of arbitrary configuration. Numerical results using a real-world antenna array are included, illustrating the excellent performance of the proposed method, both in terms of SINR and fast adaptivity to moving sources.

关键词： arrays Robustness Direction of arrival estimation Polynomials signal to noise ratio Standards Calibration

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One-Bit Radar processing and Estimation with Time-Varying Sampling thresholds

One-Bit Radar Processing and Estimation with Time-Varying Sa...

引用

sensor array and multichannel signal processing workshop

作者： Aria Ameri Jian Li Mojtaba Soltanalian University of Illinois at Chicago Chicago IL USA University of Florida Gainesville FL USA

Target parameter estimation from noisy and quantized received signals is of paramount importance in radar applications. In this paper, we propose a novel method to estimate the unknown target parameters via one-bit sampling, where the samples are produced by comparing the received signal with a time-varying threshold. the proposed approach utilizes a weighted least-squares criterion to establish a connection to previous results in radar target estimation and signal processing. Several numerical examples are provided to demonstrate the effectiveness of the proposed approach.

关键词： Radar Estimation Radar signal processing Scattering Quantization (signal) Covariance matrices

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Model Order Determination for Signed Measurements via the Bayesian Information Criterion

Model Order Determination for Signed Measurements via the Ba...

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sensor array and multichannel signal processing workshop

作者： Changheng Li Rong Zhang Jian Li Petre Stoica Department of EEIS University of Science and Technology of China Hefei Anhui P.R. china Department of ECE University of Florida Gainesville Florida USA Department of Information Technology Uppsala University Uppsala Sweden

the problem of model order selection from signed measurements obtained via L-blt sampling is considered. the extension of the Bayesian information criterion (BIC) to the case of 1-blt sampling, referred to as 1bBIC, is proposed to determine the signal model order. Numerical examples are presented to demonstrate the performance of 1bBIC when the One-Bit RELAX algorithm is used to estimate the parameters of sinusoidal signals.

关键词： signal to noise ratio Numerical models Bayes methods Maximum likelihood estimation array signal processing sensor arrays

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Time Evolution for Dynamic Probabilistic Tensors in Hierarchical Tucker Decomposition Form

Time Evolution for Dynamic Probabilistic Tensors in Hierarch...

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sensor array and multichannel signal processing workshop

作者： Felix Govaers Fraunhofer FKIE Wachtberg Germany

Many real world applications of target tracking and state estimation are non-linear filtering problems and can therefore not be solved by closed-form analytical solutions. In the recent past, tensor based approaches have become increasingly popular due to very effective decomposition algorithms, which allow the representation of discretized, high-dimensional data in compressed form. In this paper, a solution of the prediction step for a Bayesian filter is proposed, where the probability density function (pdf) is approximated by a tensor in Hierarchical Tucker Decomposition. It is shown, that the computation of the predicted pdf is about five times faster than the previously proposed Canonical Polyadic Decomposition format.

关键词： Tensile stress Probability density function Bayes methods array signal processing sensor arrays Conferences

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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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EXPERIMENTAL EVALUATION OF thE JOINT POSITION-PITCH ESTIMATION (POPI) ALGORIthM IN NOISY ENVIRONMENTS

EXPERIMENTAL EVALUATION OF THE JOINT POSITION-PITCH ESTIMATI...

引用

2008 ieee sensor array and multichannel signal processing workshop

作者： Tania Habib Marian Kepesi Lukas Ottowitz Signal Processing and Speech Communication Laboratory Graz University of Technology Austria

this paper proposes an enhancement and evaluates the performance of a recently proposed method for joint extraction of pitch and direction of arrival for speaker localization. We propose a new weighting function in order to suppress the cross-terms of the aforementioned method. the performance of the method is evaluated by measuring the correct estimate of position at a frame level. this evaluation analyzes the limits of the method at different background noise levels by using real world recordings. the results show that the proposed algorithm gives more consistent location estimates leading to a reduction in angular deviation by 4.23°at -3 dB SNR.

关键词： signal to noise ratio signal processing algorithms Microphones Joints Speech Estimation Noise measurement

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Localization of Multiple Simultaneously Active Speakers in an Acoustic sensor Network

Localization of Multiple Simultaneously Active Speakers in a...

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sensor array and multichannel signal processing workshop

作者： Andreas Brendel Sharon Gannot Walter Kellermann Multimedia Communications and Signal Processing Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Faculty of Engineering Bar-Ilan University Ramat-Gan Israel

this paper addresses the localization of an unknown number of acoustic sources in an enclosure. We extend a well established algorithm for localization of acoustic sources, which is based on the Expectation Maximization (EM) algorithm for clustering of phase differences by a Gaussian mixture model. Supporting a more appropriate probabilistic model for spherical data such as direction of arrival or phase differences, the von Mises distribution is used to derive a localization algorithm for multiple simultaneously active sources. Experiments with simulated room impulse responses confirm the superiority of the proposed algorithm to the existing method in terms of localization performance.

关键词： Microphones Direction-of-arrival estimation signal processing algorithms Time-frequency analysis Acoustics Indexes array signal processing

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Distinguishing true and false source locations when locating multiple concurrent speech sources

Distinguishing true and false source locations when locating...

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sensor array and multichannel signal processing workshop

作者： Mikael Swartling Mikael Nilsson Nedelko Grbic Department of Signal Processing School of Engineering Blekinge Institute of Technology Ronneby Sweden

A permutation problem arises in the case of locating multiple speech sources using several sensor arrays in the far field. the intersection of different direction of arrival (DOA) estimates between sensor arrays leads to a set of real source locations as well as a set of false intersections. this paper presents a novel method for pairing DOA estimates from different sensor arrays, resulting in the corresponding real intersection points. the algorithm presented is numerically efficient and suitable for real time implementations. Real room recordings are used to evaluate the method.

关键词： sensor arrays Direction of arrival estimation Time frequency analysis Speech Source separation Position measurement Speech processing

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