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检索条件"任意字段=4th IEEE Sensor Array and Multichannel Signal Processing Workshop"

共 931 条记录，以下是521-530 订阅

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Exploiting adaptive beamforming for compressive measurements

Exploiting adaptive beamforming for compressive measurements

引用

sensor array and multichannel signal processing workshop

作者： M. Sharp M. Pekala J. Nanzer I-J. Wang D. Lucarelli K. Lauritzen Applied Physics Laboratory Johns Hopkins University USA

Beamformers are spatial filters that focus energy in a particular direction while attempting to eliminate interference from other directions. this paper compares several adaptive approaches that seek to provide detection performance equivalent to classical techniques while using fewer beams, a form of measurement compression. Using an apriori distribution on the source locations together with an initial set of beams as a starting point, these algorithms adaptively form a sequence of beams based on posterior distributions of the source locations. Two methods are considered: one attempts to maximize the trace of the Fisher information and the other maximizes mutual information based on a Gaussian posterior approximation.

关键词： array signal processing Bayesian methods Libraries Approximation methods arrays Vectors Optimization

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Canonical decomposition of even higher order cumulant arrays for blind underdetermined mixture identification

Canonical decomposition of even higher order cumulant arrays...

引用

sensor array and multichannel signal processing workshop

作者： Ahmad Karfoul Laurent Albera Lieven De Lathauwer INSERM U642 Rennes France Leuven Subfaculty Science and Technology Katholieke Universiteit Leuven Kortrijk Belgium

A new family of methods, named 2q-ORBIT (q > 1), is proposed in this paper in order to blindly identify potentially underdetermined mixtures of statistically independent sources. these methods are based on the canonical decomposition of q-th order (q ges 2) cumulants. the latter decomposition is brought back to the decomposition of a third order array whose one loading matrix is unitary. Such a decomposition is then computed by alterning and repeating two schemes until convergence: the first one consists in solving a Procrustes problem while the second one needs to compute the best rank-1 approximation of several q-th order arrays. Computer results show a good efficiency of the proposed methods with respect to classical cumulant-based algorithms especially in the underdetermined case.

关键词： Matrix decomposition sensors signal to noise ratio sensor arrays signal processing algorithms Equations Convergence

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A cognitive approach for ambiguity function shaping

A cognitive approach for ambiguity function shaping

引用

sensor array and multichannel signal processing workshop

作者： A. Aubry A. De Maio B. Jiang S. Zhang Università degli Studi di Napoli Federico II Napoli Italy Industrial and Systems Engineering University of Minnesota Minneapolis Minneapolis MN USA

In this paper, we propose a cognitive approach to design phase-only modulated waveforms sharing a desired ambiguity function. We formulate the problem as a quartic order polynomial optimization problem with a constant modulus constraint on each variable. thus, we devise an optimization procedure based on the Maximum Block Improvement (MBI) approach. At the analysis stage, we assess the performance of the proposed technique showing its capability to properly shape the ambiguity function of the transmitted waveform.

关键词： Optimization Radar Doppler effect Algorithm design and analysis Polynomials Vectors signal processing algorithms

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An Anti-jamming Method of ISAR Imaging with FDA-MIMO Radar

An Anti-jamming Method of ISAR Imaging with FDA-MIMO Radar

引用

sensor array and multichannel signal processing workshop

作者： Guangming Li Qun Zhang Ying Luo Kaiming Li Linghua Su Rui Li Graduate college Air Force Enginnering University Xi'an China Information and Navigation college Air Force Enginnering University Xi'an China

In recent years, the frequency diverse array (FDA) radar has attracted much attention due to its range-angle dependent beam-pattern. And multiple input multiple output (MIMO) radar has been widely investigated with the advantage of transmit waveform diversity. In this paper, a FDA-MIMO Inverse Synthetic Aperture Radar (ISAR) is proposed to achieve anti-jamming of ISAR imaging. LFM (Linear Frequency Modulated) and SFCS (Stepped-Frequency Chirp signal) signals are transmitted to jammer and targets respectively, and the received signals are matched filtering by the signal transmitted to the targets. So the jamming signal can't matched with the reference signal, the well anti-jamming effect can be obtained. the performance of the proposed method is evaluated by the simulation results.

关键词： Jamming Radar imaging array signal processing Imaging Radar signal processing Frequency modulation

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Patterned complex-valued matrix derivatives

Patterned complex-valued matrix derivatives

引用

sensor array and multichannel signal processing workshop

作者： Are Hjorungnes Daniel P. Palomar UniK - University Graduate Center University of Oslo Kjeller Norway Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong China

A systematic and simple method is proposed for how to find the derivative of complex-valued matrix functions which depend on matrix arguments that contain patterns. the proposed method is developed by means of the chain rule and it is able to handle both linear and nonlinear patterns. One main issue of the proposed method is to identify a matrix function which depends on independent variables and its domain must have the same dimension as the dimension of the set of patterned matrices. In addition, this function must produce all the matrices within the pattern of interest. Some illustrative examples which are relevant for problems in the area of signal processing for communications are presented.

关键词： Matrices Jacobian matrices Symmetric matrices signal processing Matrix decomposition Presses Vectors

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A moving horizon convex relaxation for mobile sensor network localization

A moving horizon convex relaxation for mobile sensor network...

引用

sensor array and multichannel signal processing workshop

作者： Andrea Simonetto Geert Leus Delft University of Technology Delft The Netherlands

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： Mobile communication Mobile computing Estimation Kalman filters Vectors Computational complexity Noise

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Multi-Layer Terahertz Imaging of Non-Overlapping Contents

Multi-Layer Terahertz Imaging of Non-Overlapping Contents

引用

sensor array and multichannel signal processing workshop

作者： Pu Wang Haoyu Fu Toshiaki Koike-Akino Philip V. Orlik Mitsubishi Electric Research Laboratories (MERL) Cambridge MA USA Ohio State University Columbus OH USA

this paper considers terahertz (thz) imaging of multi-layer nonoverlapping contents with compressed measurements. One issue here is the shadow effect from front layers to deep layers due to the non-uniform penetrating illumination. In the case of nonoverlapping contents in layered structures, the shadow effect can be utilized to improve recovery performance and reduce the number of measurements. To this end, we propose several approaches based on the total variation (TV) minimization principle and take into account individual-layer sparsity, group sparsity over layers, and hierarchical group sparsity over layers to reduce the number of measurements. Numerical evaluation confirms the effectiveness of the proposed approaches.

关键词： TV Minimization Indexes Biomedical measurement array signal processing sensor arrays

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Comparison of Sparse arrays From Viewpoint of Coarray Stability and Robustness

Comparison of Sparse Arrays From Viewpoint of Coarray Stabil...

引用

sensor array and multichannel signal processing workshop

作者： Chun-Lin Liu P. P. Vaidyanathan Dept. of Electrical Engineering MC 136–93 California Institute of Technology Pasadena CA USA

Sparse arrays, such as minimum redundancy arrays (MRA), nested arrays, and coprime arrays, can resolve O(N 2 ), uncorrelated sources with N physical sensors, since they possess an O(N 2 ) -long uniform segment in the difference coarray, which is defined as the differences between sensor locations. Empirically, this O(N 2 ), property is susceptible to sensor failures. On the other hand, uniform linear arrays (ULA) are known to be robust, but they possess only O(N) elements in the difference coarray. this paper compares the size and the robustness of the difference coarray for a wide variety of array geometries. It is observed from numerical examples that, for a fixed N, increasing the size of the difference coarray typically makes it less robust to faulty sensors. Furthermore, it is noticed from examples that given two arrays with the same N and the same difference coarray, one could be much more robust than the other.

关键词： sensor arrays Robustness array signal processing Redundancy Geometry Conferences

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On the generalization of blind source separation algorithms from instantaneous to convolutive mixtures

On the generalization of blind source separation algorithms ...

引用

sensor array and multichannel signal processing workshop

作者： Tiemin Mei Alfred Mertins Fuliang Yin Institute for Signal Processing University of Lübeck Lubeck Germany School of Information Science and Engineering Shenyang Ligong University Shenyang China School of Electronic and Information Engineering Dalian University of Technology Dalian China

Many convolutive blind source separation (BSS) approaches are generalized from instantaneous BSS methods in either time or frequency domain. In this paper, we establish in a general way the inner relationship between the time-domain instantaneous BSS and the frequency-domain convolutive BSS. From this point of view, the time-domain approaches for instantaneous mixture separation are generalized to those for convolutive mixture separation in the frequency domain. Two examples are given to illustrate the feasibility of the proposed approach.

关键词： Frequency domain analysis Source separation Time domain analysis Blind source separation Finite impulse response filter signal processing algorithms Joints

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Sparse Bayesian Learning for DOA Estimation with Recursive Grid-Refining

Sparse Bayesian Learning for DOA Estimation with Recursive G...

引用

sensor array and multichannel signal processing workshop

作者： Lan Wang Jinghao Zheng Fangfang Chen Jisheng Dai Department of Electronic Engineering Jiangsu University Zhenjiang China

the modeling error for off-grid direction-of-arrival (DOA) estimation can be alleviated by the technique of linear approximation, but cannot be fully eliminated, especially for coarse grids. In this paper, we not only adopt a linear approximation to cover the off-grid gap, but also try to combine it with the idea that all the sampled locations can be viewed as the adjustable parameters. then, we utilize an expectation-maximization (EM) to recursively refine the grid points, rather than updating the coefficients in the linear approximation directly. In this way, the refined grid points will tend to the true DOAs after several iterations. Simulation results illustrate that the proposed method can give a fast DOA estimation while remain a reasonable accuracy.

关键词： Direction-of-arrival estimation Estimation Linear approximation Bayes methods Computational modeling sensor arrays array signal processing

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