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检索条件"任意字段=2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014"

共 111 条记录，以下是51-60 订阅

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Direction finding and array calibration based on sparse reconstruction in partly calibrated arrays

Direction finding and array calibration based on sparse reco...

引用

sensor array and multichannel signal processing workshop

作者： Christian Steffens Pouyan Parvazi Marius Pesavento Communication Systems Group Technische Universität Darmstadt Germany

A novel convex optimization problem formulation for source localization using partly calibrated arrays composed of subarrays with unknown displacements is introduced. the proposed formulation is based on sparse reconstruction using a mixed trace- and ℓ 1 -norm minimization and exploits joint sparsity and special structure in the signal model. the new technique is applicable to subarrays of arbitrary topologies and allows the joint estimation of the directions of arrival (DoAs) and the array calibration. As shown by simulations, our new DoA estimation technique outperforms the state of the art method RARE, especially in low number of snapshot and low signal-to-noise ratio regime.

关键词： arrays Estimation Direction-of-arrival estimation Principal component analysis Vectors Minimization

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Wideband waveform design for clutter suppression

Wideband waveform design for clutter suppression

引用

sensor array and multichannel signal processing workshop

作者： Marie Ström Ashkan Panahi Mats Viberg Kent Falk Saab EDS Göteborg Sweden Signal Processing Group Chalmers University Goteborg Sweden

Modern signal generators offer the capability to synthesize arbitrary wideband waveforms for radar and sonar applications. this makes it possible to optimize signals for specific purposes or scenarios. Herein, we discuss how to design a wideband waveform for clutter suppression. We formulate an optimization in terms of mainlobe and sidelobe properties of the ambiguity function, then we provide an approximate solution based on convex relaxation. Numerical evaluation shows the advantage of selecting a smart signal compared to a conventional waveform design. the advantages are shown as a lower probability of false alarm and a higher probability of correct target detection.

关键词： Clutter Optimization signal to noise ratio Wideband Receivers

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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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Ultrasonic array imaging for immersion non-destructive testing

Ultrasonic array imaging for immersion non-destructive testi...

引用

sensor array and multichannel signal processing workshop

作者： Nasim Moallemi Shahram Shahbazpanahi Faculty of Engineering and Applied Science University of Ontario Institute of Technology Oshawa ON Canada

One of the applications of advanced array signal processing is immersion ultrasonic non-destructive testing (NDT), where a solid test sample and an array of transducers are immersed in water, for the purpose of imaging the test sample. To do so, the knowledge of the shape of the upper surface of the test sample is needed. We model the interface between water and the solid as an incoherently spatially distributed reflector. We then develop a covariance fitting based approach to estimate the parameters of the shape of the upper surface of the test sample. With the knowledge of the estimated shape of this surface, we use the same approach to estimate the parameters of the shape of a crack inside the test sample. Numerical simulations are conducted to show the accuracy of the proposed approach.

关键词： Shape Surface cracks arrays Solids Transducers Acoustics

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Massive MIMO meets decision fusion: Decode-and-fuse vs. decode-then-fuse

Massive MIMO meets decision fusion: Decode-and-fuse vs. deco...

引用

sensor array and multichannel signal processing workshop

作者： Domenico Ciuonzo Pierluigi Salvo Rossi Subhrakanti Dey Department of Industrial and Information Engineering Second University of Naples Italy Department of Engineering Sciences Uppsala University Sweden

We study channel-aware decision fusion over a multiple-input multiple-output (MIMO) channel in the largearray regime at the decision-fusion center (DFC). Inhomogeneous large-scale fading between the sensors and the DFC is consider in addition to the small-scale fading, and pilot-based channel estimation is performed at the DFC. Linear processing techniques are analyzed in order to design low-complexity alternatives to the optimum log-likelihood ratio test (LLRT). Performance evaluation based on Monte Carlo simulations are presented.

关键词： arrays Wireless sensor networks Fading MIMO Channel estimation Receiving antennas Complexity theory

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Scalar-gain distributed estimators for Hermitian systems

Scalar-gain distributed estimators for Hermitian systems

引用

sensor array and multichannel signal processing workshop

作者： Usman A. Khan Department of Electrical and Computer Engineering Tufts University Medford MA

In this paper, we consider distributed estimation of discrete-time, LTI state-spaces, restricted to Hermitian (or symmetric) system matrices. We assume that the underlying system is monitored by a group of agents, sparsely connected via an undirected communication graph, and no agent may possess enough measurements (in its neighborhood) to estimate the entire state-vector. In this context, we analyze an estimation protocol that only requires a single design parameter: a scalar-gain, α ∈ R. We design this scalar-gain, α, with the help of some eigenvalue (Weyl's) inequalities and derive the conditions under which a scalar-gain is sufficient to estimate the underlying system with bounded estimation error.

关键词： Eigenvalues and eigenfunctions Linear matrix inequalities Conferences Estimation Stability analysis signal processing Context

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Max-flow min-cut for power system security index computation

Max-flow min-cut for power system security index computation

引用

sensor array and multichannel signal processing workshop

作者： Oliver Kosut School of Electrical Arizona State University Tempe AZ

the security index problem for false data injection attacks on power systems is considered. In particular, the problem is to find the minimum cost set of bus injection meters and line flow meters that an attacker can seize so as to execute a false data injection. A polynomial-time algorithm is provided to solve this problem in certain settings, based on the principle of max-flow min-cut. the security index problem is shown to be equivalent to a min-cut problem, and that this problem can be solved using a generalization of the classic max-flow min-cut algorithm in which flows are successively augmented until doing so is no longer possible.

关键词： Security Indexes signal processing algorithms Power systems Vectors Observability Transmission line measurements

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Improving the projection method for TOA source localization in the presence of sensor position errors

Improving the projection method for TOA source localization ...

引用

sensor array and multichannel signal processing workshop

作者： Jinzhou Li K.C. Ho Fucheng Guo Wenli Jiang ECE Department University of Missouri Columbia MO USA School of Electronic Science and Engineering National University of Defense Technology Changsha Hunan China

this paper develops a closed-form solution that improves the projection matrix method for time of arrival (TOA) source localization in the presence of sensor position inaccuracy. the projection approach is attractive because it does not require the use of an extra variable as in the traditional closed-form solution. Compared with the previous projection method, the proposed algorithm offers a closed-form solution and at the same time attains the Cramer-Rao lower bound (CRLB) performance for Gaussian noise over the small noise region. the performance of the proposed method is validated by simulations.

关键词： Position measurement Accuracy Estimation signal processing algorithms Noise Vectors Covariance matrices

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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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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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Ridge regression and Kalman filtering for target tracking in wireless sensor networks

Ridge regression and Kalman filtering for target tracking in...

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sensor array and multichannel signal processing workshop

作者： Sandy Mahfouz Farah Mourad-Chehade Paul Honeine Joumana Farah Hichem Snoussi Institut Charles Delaunay (CNRS) Université de Technologie de Troyes Troyes France Department of telecommunications Universite Saint-Esprit de Kaslik Lebanon

this paper introduces an original method for target tracking in wireless sensor networks that combines machine learning and Kalman filtering. A database of radio-fingerprints is used, along with the ridge regression learning method, to compute a model that takes as input RSSI information, and yields, as output, the positions where the RSSIs are measured. this model leads to a position estimate for each target. the Kalman filter is used afterwards to combine the model's estimates with predictions of the target's positions based on acceleration information, leading to more accurate ones.

关键词： Kalman filters Target tracking Wireless sensor networks Acceleration Vectors Noise Computational modeling

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