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

共 2592 条记录，以下是171-180 订阅

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Identical Partitioning of Consecutive Integer Set 13

Identical Partitioning of Consecutive Integer Set

引用

13rd IEEE sensor array and multichannel signal processing workshop (SAM)

作者： Zhang, Yimin D. Sun, Shunqiao Temple Univ Dept Elect & Comp Engn Philadelphia PA 19122 USA Univ Alabama Dept Elect & Comp Engn Tuscaloosa AL 35487 USA

ISBN: (纸本)9798350344820;9798350344813

In this paper, we develop a scheme to partition a one- or multi-dimensional consecutive integer number set into multiple identical, possibly rotated, subsets. The proposed technique first exploits one-dimensional nested subsets, and the results are extended to achieve two- and multi-subset partitioning as well as in two- and multi-dimensional spaces. The number of consecutive lags in each case is examined. The results are useful to various sensing and communication applications, and sparse step-frequency waveform design for range estimation in automotive radar is demonstrated as an example.

关键词： integer set partition multi-dimensional partition sparse array sparse waveform design automotive radar

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SPARSE BAYESIAN LEARNING FOR DOA ESTIMATION USING CO-PRIME AND NESTED arrayS 10

SPARSE BAYESIAN LEARNING FOR DOA ESTIMATION USING CO-PRIME A...

引用

10th IEEE sensor array and multichannel signal processing workshop (SAM)

作者： Nannuru, Santosh Gerstoft, Peter Koochakzadeh, Ali Pal, Piya Univ Calif San Diego Scripps Inst Oceanog La Jolla CA 92093 USA Univ Calif San Diego Elect & Comp Engn La Jolla CA 92093 USA

ISBN: (纸本)9781538647523

Sparse Bayesian learning (SBL) has been used to obtain source direction-of-arrivals (DoAs) from uniform linear array (ULA) data. The maximum number of sources that can be resolved using a ULA is limited by the number of sensors in the array. It is known that sparse linear arrays such as co-prime and nested arrays can resolve more sources than the number of sensors. In this paper we demonstrate this using SBL. We compute the mean squared error in source power estimation as various parameters are varied.

关键词： Sparse Bayesian learning co-prime array nested array DoA estimation compressed sensing

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A CLOSED-FORM SOLUTION FOR MULTILINEAR PARAFAC DECOMPOSITIONS

A CLOSED-FORM SOLUTION FOR MULTILINEAR PARAFAC DECOMPOSITION...

引用

IEEE sensor array and multichannel signal processing workshop

作者： Roemer, Florian Haardt, Martin Tech Univ Ilmenau Commun Res Lab D-98684 Ilmenau Germany

ISBN: (纸本)9781424422401

In this paper we study the R-way Parallel Factor Analysis (also referred to as R-way PARAFAC) problem. This branch of multi-way signal processing has received increased attention recently which is due to the versatility of the model as well as the identifiability results demonstrating its superiority to matrix-only (2-way) approaches. In R-way PARAFAC analysis, the goal is to decompose an R-dimensional tensor into a minimal sum of rank-1 terms. So far, there exist sub-optimal closed-form solutions as well as iterative techniques for finding these decompositions. However, the latter often require many iterations to converge. In this contribution we demonstrate that the R-way PARAFAC decomposition can be reduced to a set of simultaneous matrix diagonalization problems. Exploiting the structure of the R-dimensional problem, we obtain several estimates for each of the factors and present a "best matching" scheme to select the best estimate for each factor. By means of computer simulations we compare our closed-form solution to an iterative technique and demonstrate the enhanced robustness in critical scenarios.

关键词： Multidimensional signal processing Parameter estimation array signal processing

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Non-Coherent Source Localization with Distributed sensor array Networks 12

Non-Coherent Source Localization with Distributed Sensor Arr...

引用

IEEE 12th sensor array and multichannel signal processing workshop (SAM)

作者： Wan, Zhengyu Liu, Wei Willett, Peter Univ Sheffield Dept Elect & Elect Engn Sheffield S Yorkshire England Univ Connecticut Dept Elect & Comp Engn Storrs CT USA

ISBN: (纸本)9781665406338

The non-coherent source localization problem based on distributed sensor arrays can be formulated into a group sparsity based phase retrieval problem where only the magnitude (absolute value) of the received signals is available. Under such a framework, a two-dimensional localization method is proposed. Unlike traditional source localization methods, random phase errors at sensors of the distributed array will not affect estimation results by the proposed method. Simulation results indicate that the proposed non-coherent source localization method outperforms the traditional one in the presence of large phase errors, while still maintains an acceptable accuracy in the absence of phase errors.

关键词： Target localization distributed sensor array magnitude-only measurements group sparsity non-coherent detection

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Beamformer Design For Nonstationary signals by Means of Interfrequency Correlations

Beamformer Design For Nonstationary Signals by Means of Inte...

引用

IEEE 7th sensor array and multichannel signal processing workshop (SAM)

作者： Naghibi, Tofigh Pfister, Beat ETH Comp Engn & Networks Lab Speech Proc Grp Zurich Switzerland

ISBN: (纸本)9781467310710

The wide-sense stationary assumption has been frequently employed in array processing, since it results in uncorrelated frequency bins and consequently major simplifications arise. However, unlike stationary signals, significant interfrequency correlations are observable in nonstationary signals like speech. Here, we drop the stationarity assumption and will show that taking interfrequency correlations into account leads to higher noise reduction. We develop a framework to design nonstationary beamformers similar to the stationary Frost beamformers. Based on the noise model, it can be used to design both fixed and adaptive beamformers. The nonstationary beamformer derived here is a set of time-varying filters and hence can be seen as a set of time-frequency or wavelet transform filters.

关键词： beamformers Noise models time-varying filters array processing signals setting time Noise reduction Filters

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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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4th IEEE sensor array and multichannel signal processing workshop

作者： Park, Cheol-Sun Jang, Won Kim, Dae-Young Agcy Def Dev EW Lab Taejon South Korea Chungnam Natl Univ Dept Informat & Commun Engn Chungnam 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 2 pi. 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： antenna array directional of array (DOA) estimation NLA( nonuniform linear array)

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Direction of Arrival Estimation with Microphone arrays Using SRP-PHAT and Neural Networks 10

Direction of Arrival Estimation with Microphone Arrays Using...

引用

10th IEEE sensor array and multichannel signal processing workshop (SAM)

作者： Diaz-Guerra, David Beltran, Jose R. Univ Zaragoza Dept Elect Engn & Commun Zaragoza Spain

ISBN: (纸本)9781538647523

The Steered Response Power with phase transform (SRP-PHAT) is one of the most employed techniques for Direction of Arrival (DOA) estimation with microphone arrays due its robustness against acoustical conditions as reverberation or noise. Among its main drawbacks is the growth of its computational complexity when the search space increases. To solve this issue, we propose the use of Neural Networks (NN) to obtain the DOA as a regression problem from a low resolution SRP-PHAT power map. The NNs can learn and exploit the information of the acoustic reflections of the room where the array is located with a training method that can be easily performed by an end user without technical knowledge.

关键词： microphone array direction of arrival DOA Sound Source Localization SSL SRP SRP-PHAT neural netowrks tele-conference system Wireless Acoustic sensor Network WASN WSN

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Optical array aspects of Computed Spectroscopy™

Optical array aspects of Computed Spectroscopy™

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4th IEEE sensor array and multichannel signal processing workshop

作者： Hoctor, Ralph T. Wheeler, Frederick W. Barrett, Eamon B. GE Global Res Niskayuna NY 12309 USA ATC Lockheed Martin Space Syst Sunnyvale CA 94089 USA

ISBN: (纸本)1424403081

Computed Spectroscopy (TM) (CS) is a new approach to hyperspectral imaging recently introduced by the authors [1]*. 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 [2], and a previous publication by the present authors [1] features a brief coarTay-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： array processing

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A Moving Horizon Convex Relaxation for Mobile sensor Network Localization

A Moving Horizon Convex Relaxation for Mobile Sensor Network...

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8th IEEE sensor array and multichannel signal processing workshop (SAM)

作者： Simonetto, Andrea Leus, Geert Delft Univ Technol Fac EEMCS NL-2826 CD Delft Netherlands

ISBN: (纸本)9781479914814

In mobile sensor network localization problems we seek to estimate the position of the mobile sensor nodes by using a subset of pair-wise range measurements (among the nodes and with mobile anchors). When the sensor nodes are static, convex relaxations have been shown to provide a remarkably accurate approximate solution to this NP-hard estimation problem. In this paper, we propose a novel convex relaxation to tackle the more challenging dynamic case and we develop a moving horizon convex estimator based on a maximum a posteriori (MAP) formulation. The resulting estimator is then compared to standard extended and unscented Kalman filters both with respect to computational complexity and performance with simulated data. The results are promising, yet a more detailed analysis is needed.

关键词： sensor networks Convexity Mobile Ganglia Kalman filters Horizon complexity classes Moving Relaxation

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Joint Range, Angle and Doppler Estimation for FDA-MIMO Radar 10

Joint Range, Angle and Doppler Estimation for FDA-MIMO Radar

引用

10th IEEE sensor array and multichannel signal processing workshop (SAM)

作者： Xu, Jian Wang, Wen-Qin Cui, Can Gui, Ronghua Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu 611731 Sichuan Peoples R China

ISBN: (纸本)9781538647523

Frequency diverse array (FDA) radar for joint range and angle estimation has drawn much attention, but Doppler estimation is often ignored in the literature. In this paper, we propose joint range, angle and Doppler estimation for FDA-multiple-input multiple-output (FDA-MIMO) radar. In order to reduce the computation complexity, the Doppler is independently estimated firstly by the extended invariance principle instead of maximum likelihood (ML) estimator. Next, the range and angle are estimated separately with the unstructured model. That is, the three-dimensional search problem of joint range, angle and Doppler estimation is simplified into three one-dimensional search problems. The superiorities of the proposed method over conventional ML algorithms are verified by numerical results.

关键词： Doppler effect Doppler radar array signal processing Maximum likelihood estimation sensor arrays"

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