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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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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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Localization and array shape estimation using software defined radio array testbed

Localization and array shape estimation using software defin...

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sensor array and multichannel signal processing workshop

作者： Akinbiyi Akindoyin Marc Willerton Athanassios Manikas Electrical and Electronics Engineering Imperial College London Imperial College London London London GB

The emergence of software defined radio (SDR) aims to increase flexibility as well as reduce cost, size, weight and power (SWAP) inherent in traditional hardware radios. This paper is concerned with addressing issues associated with the formation of an array system from multiple SDR boards where each has an independent local oscillators (LO) in a multi-antenna system using representative examples such as localization and array shape estimation. In particular, practical experimental results are initially presented for estimating the unknown location of a single source using an SDR array of known array geometry. Furthermore, in the case that the SDR array geometry is unknown, a novel array shape estimation algorithm is proposed. The proposed algorithm estimates the antenna locations without requiring any external sources. This is achieved by allowing the array elements operate as transceivers.

关键词： arrays signal processing Conferences Software Vectors Shape Estimation

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Statistical angular resolution limit for array radar with ultrawideband stochastic signals

Statistical angular resolution limit for array radar with ul...

引用

sensor array and multichannel signal processing workshop

作者： Xiaoli Zhou Hongqiang Wang Yongqiang Cheng Yuliang Qin Haowen Chen Bin Sun School of Electronic Science and Engineering National University of Defense Technology Changsha China

The 2-D angular resolution limit for array radar with ultrawideband (UWB) stochastic signals based on the statistical resolution theory is presented in this paper. The signal model of monostatic array radar with circular array configuration and UWB stochastic signals is established, while the resolution of two closely spaced targets is modelled as a binary hypothesis test. The statistical angular resolution limit (SARL) for array radar with UWB stochastic signals is derived based on the generalized likelihood ratio test (GLRT) with given probabilities of false alarm and detection. The effects of detection parameters, transmit waveforms, array geometry, signal-to-noise ratio and parameters of target on SARL are analysed. Compared with the conventional resolution defined by ambiguity function, the SARL reflects the practical resolution ability of radar and can provide an optimization criterion for radar system design.

关键词： arrays signal resolution Manganese Radar cross-sections Stochastic processes

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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...

引用

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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Performance analysis of time frequency subspace based direction finding algorithms in presence of perturbed array manifold

Performance analysis of time frequency subspace based direct...

引用

sensor array and multichannel signal processing workshop

作者： Adel Belouchrani Mohamed Khodja Electrical Engineering Department Ecole Nationale Poly technique Algiers Algeria

Conventional subspace based direction finding approaches such as MUSIC and ESPRIT algorithms commonly use the array data covariance matrix. In non stationary context, the use of the Spatial Time-Frequency Distribution (STFD) instead of the covariance matrix can significantly improve the performance of such algorithms. In this paper we are interested in the performance analysis of such approaches in the presence of both additive noise and perturbed array manifold. An unified expression of the Direction Of Arrival (DOA) error estimation is derived for both approaches. The obtained results show that for low signal to Noise Ratio (SNR) and high signal to sensor Perturbation Ratio (SPR) the STFD based DOA estimations perform better, while for high SNR and for the same SPR both Covariance and STFD based approaches have similar performance.

关键词： arrays signal to noise ratio Direction-of-arrival estimation Time-frequency analysis Covariance matrices Multiple signal classification Algorithm design and analysis

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Energy detection for decision fusion in wireless sensor networks over Ricean-mixture fading

Energy detection for decision fusion in wireless sensor netw...

引用

sensor array and multichannel signal processing workshop

作者： Pierluigi Salvo Rossi Domenico Ciuonzo Torbjörn Ekman Kimmo Kansanen Department of Industrial and Information Engineering Second University of Naples Italy Department of Electronics and Telecommunications Norwegian University of Science and Technology Norway

In this paper we focus on the energy detector for decision fusion in wireless sensor networks over multiple access channels. More specifically, we derive analytical performance in terms of global probability of false alarm and detection (including asymptotic performance for large number of sensors) when the fading is a Ricean mixture, i.e. channel coefficients are sampled from a Gaussian mixture (GM) distribution. The motivation for the GM is the ability to model real-world scenarios while keeping mathematical tractability. Analytical results are confirmed through numerical simulations.

关键词： Rayleigh channels signal to noise ratio Detectors Vectors arrays

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SINR optimization in wideband full-duplex MIMO relays under limited dynamic range

SINR optimization in wideband full-duplex MIMO relays under ...

引用

sensor array and multichannel signal processing workshop

作者： Emilio Antonio-Rodríguez Roberto López-Valcarce Taneli Riihonen Stefan Werner Risto Wichman Department of Signal Theory and Communications University of Vigo Vigo Spain Department of Signal Processing and Acoustics Aalto University Helsinki Finland

We develop a method for self-interference mitigation in wideband full-duplex multiple-input multiple-output regenerative relays, taking into account transmitter impairments and limited receiver dynamic range. The method combines a cancellation and suppression architecture by incorporating feedforward filters at both sides of the relay. The design criterion is to maximize the signal-to-interference-plus-noise ratio (SINR) at the relay input. On the transmit side, linear constraints are imposed in order to control the effect on the information signal at destination. Simulation results show the effectiveness of the proposed method both in terms of self-interference reduction and SINR improvement.

关键词： Relays Interference signal to noise ratio Dynamic range MIMO Receivers

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Strategies for principal component analysis in wireless sensor networks

Strategies for principal component analysis in wireless sens...

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sensor array and multichannel signal processing workshop

作者： Nisrine Ghadban Paul Honeine Clovis Francis Farah Mourad-Chehade Joumana Farah Universite Libanaise Beirut LB Institut Charles Delaunay (CNRS) Université de technologie de Troyes CNRS France Faculté de Génie Université Libanaise Lebanon Telecommunications department Faculty of Engineering Holy-Spirit University of Kaslik Lebanon

This paper deals with the issue of monitoring physical phenomena using wireless sensor networks. It provides principal component analysis for the time series of sensors' measurements. Without the need to compute the sample covariance matrix, we derive several in-network strategies to estimate the principal axis, including noncooperative and diffusion strategies. The performance of the proposed strategies is illustrated in the issue of monitoring gas diffusion.

关键词： Wireless sensor networks Principal component analysis Covariance matrices Temperature measurement Convergence Time series analysis Pollution measurement

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CS based specular multipath exploitation in TWRI under wall position uncertainties

CS based specular multipath exploitation in TWRI under wall ...

引用

sensor array and multichannel signal processing workshop

作者： Michael Leigsnering Fauzia Ahmad Moeness G. Amin Abdelhak M. Zoubir Signal Processing Group Technische Universitat Darmstadt Darmstadt Germany Center for Advanced Communications Villanova University Villanova PA USA

Through-the-wall radar imaging utilizes electromagnetic wave propagation to reveal the locations of obscured targets. Indirect signal propagation paths, usually considered a nuisance, may be used to improve the quality of through-the-wall radar images. However, imperfect knowledge of the surrounding scatterers, i.e. the interior walls of a building, has adverse effects on such multipath exploitation schemes. We propose a joint scene reconstruction and wall position estimation approach based on compressive sensing. This enables effective and reliable utilization of indirect propagation paths resulting in clutter-free images of stationary indoor scenes. Simulation results demonstrate the effectiveness of the proposed method.

关键词： Image reconstruction Radar imaging arrays Vectors signal processing Transmitters

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