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the LOCATA Challenge Data Corpus for Acoustic Source Localization and Tracking

The LOCATA Challenge Data Corpus for Acoustic Source Localiz...

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sensor array and multichannel signal processing workshop

作者： Heinrich W. Löllmann Christine Evers Alexander Schmidt Heinrich Mellmann Hendrik Barfuss Patrick A. Naylor Walter Kellermann Friedrich-Alexander University Erlangen-Nürnberg Imperial College London Humboldt-Universität zu Berlin

Algorithms for acoustic source localization and tracking are essential for a wide range of applications such as personal assistants, smart homes, tele-conferencing systems, hearing aids, or autonomous systems. Numerous algorithms have been proposed for this purpose which, however, are not evaluated and compared against each other by using a common database so far. the ieee-AASP Challenge on sound source localization and tracking (LOCATA) provides a novel, comprehensive data corpus for the objective benchmarking of state-of-the-art algorithms on sound source localization and tracking. the data corpus comprises six tasks ranging from the localization of a single static sound source with a static microphone array to the tracking of multiple moving speakers with a moving microphone array. It contains real-world multichannel audio recordings, obtained by hearing aids, microphones integrated in a robot head, a planar and a spherical microphone array in an enclosed acoustic environment, as well as positional information about the involved arrays and sound sources represented by moving human talkers or static loudspeakers.

关键词： arrays Microphone arrays Task analysis array signal processing Acoustics Databases

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Efficient Relative Fingerprinting Based UAV Localization via Tensor Completion

Efficient Relative Fingerprinting Based UAV Localization via...

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sensor array and multichannel signal processing workshop

作者： Changju Kan Guoru Ding Fei Song Junfei Qiu College of Communications Engineering Army Engineering University of PLA Nanjing China Department of Electronic Engineering University of York York U.K.

Recently, unmanned Aerial Vehicles (UAVs) localization is becoming a major research focus. In this paper, we propose a novel efficient relative fingerprinting-based passive UAV localization algorithm via a tensor completion approach. We first introduce a new relative fingerprint framework by exploring the correlations between the UAV fingerprint and the fingerprint database, the correction factors can be achieved to apply the fingerprint idea into the passive localization case. then, we exploit the spatial correlation of the RSS data and propose a new training scheme which utilizes tensor completion. Simulation results highlight the superior performance of the proposed algorithm in terms of reconstruction error and localization accuracy.

关键词： Correlation Tensile stress sensors Databases Training Unmanned aerial vehicles signal processing algorithms

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Blind detection of exclusive source activity periods in reverberant acoustic environments

Blind detection of exclusive source activity periods in reve...

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sensor array and multichannel signal processing workshop

作者： Robert M. Nickel Department of Electrical Engineering Bucknell University Lewisburg PA USA

Blind separation and dereverberation of acoustic sources is still considered a very challenging task despite many years of research and the availability of increasingly powerful computation engines. the complexity of the task can be significantly reduced for sources that exhibit sufficiently long exclusive activity periods (EAPs). EAPs are time intervals during which only one source is active and all other sources are inactive (i.e. zero). During EAPs the estimation of the underlying system parameters simplifies from a MIMO type to a SIMO type. the existence of EAPs is not guaranteed for arbitrary signal classes. EAPs occur very frequently, however, in recordings of conversational speech. In this paper we propose a new low complexity method for EAP detection which significantly outperforms earlier approaches.

关键词： Speech Mathematical model Equations Speech processing Acoustics Nickel Transfer functions

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Constrained Least Squares for Extended Complex Factor Analysis

Constrained Least Squares for Extended Complex Factor Analys...

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sensor array and multichannel signal processing workshop

作者： Ahmad Mouri Sardarabadi Alle-Jan van der Veen L. V.E. Koopmans Kapteyn Astronomical Institute University of Groningen The Netherlands Delft University of Technology Delft The Netherlands

For subspace estimation with an unknown colored noise, Factor Analysis (FA) and its extensions, denoted as Extended FA (EFA), are good candidates for replacing the popular eigenvalue decomposition (EVD). Finding the unknowns in (E)FA can be done by solving a non-linear least square problem. For this type of optimization problems, the Gauss-Newton (GN) algorithm is a powerful and simple method. the most expensive part of the GN algorithm is finding the direction of descent by solving a system of equations at each iteration. In this paper we show that for (E)FA, the matrices involved in solving these systems of equations can be diagonalized in a closed form fashion and the solution can be found in a computationally efficient way. We show how the unknown parameters can be updated without actually constructing these matrices. the convergence performance of the algorithm is studied via numerical simulations.

关键词： array signal processing sensor arrays Conferences Ions Indexes Integrated circuits

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the correlation preserving transform resolves phase ambiguity in complex decorrelating transforms

The correlation preserving transform resolves phase ambiguit...

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sensor array and multichannel signal processing workshop

作者： C. Cheong Took S. C. Douglas D. P. Mandic Department of Computing University of Surrey UK Department of Electrical Engineering Southern Methodist University USA Department of Electronic Engineering Imperial College London UK

A solution to the problem of intraference is obtained by recognising that the current diagonalisation schemes for the complex symmetric pseudocovariance matrix are not adequate to preserve its intrinsic complex-valued nature. To this end, we propose the correlation preserving transform (CPT), which both maintains the degree of the intrinsic correlation within a recovered bivariate source (minimum intraference) and minimises the correlation between different bivariate sources (minimum interference). Unlike the existing literature, this work therefore considers both the correlation structure between the data channels within bivariate sources and inter-source correlation. the efficacy of the proposed method is validated through analysis and simulations.

关键词： Correlation Transforms signal processing Symmetric matrices Covariance matrices Matrix decomposition Approximation methods

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Decision Fusion for Carbon Dioxide Release Detection from Pressure Relief Devices

Decision Fusion for Carbon Dioxide Release Detection from Pr...

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sensor array and multichannel signal processing workshop

作者： Gianluca Tabella Yuri Di Martino Domenico Ciuonzo Nicola Paltrinieri Xiaodong Wang Pierluigi Salvo Rossi Dept. Electronic Systems Norwegian University of Science and Technology Trondheim Norway Dept. Electrical Engineering Columbia University New York NY USA Dept. Electrical Engineering and Information Technologies (DIETI) University of Naples &#x201C Federico II&#x201D Naples Italy Dept. Mechanical and Industrial Engineering Norwegian University of Science and Technology Trondheim Norway Dept. Gas Technology SINTEF Energy Research Norway

this work investigates the distributed detection of carbon dioxide (CO 2 ) release from storage tanks caused by the opening of pressure relief devices via inexpensive sensor devices in an industrial context. A realistic model of the dispersion is put forward in this paper. Both full-precision and rate-limited setups for sensors are considered, and fusion rules capitalizing the dis-persion model are derived. Simulations analyze the performance trends with relevant system parameters.

关键词： Performance evaluation Analytical models array signal processing Conferences Carbon dioxide Market research Carbon

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Hierarchical particle filtering for target tracking in multi-modal sensor networks

Hierarchical particle filtering for target tracking in multi...

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sensor array and multichannel signal processing workshop

作者： Phani Chavali Arye Nehorai Preston M. Green Department of Electrical and Systems Engineering Washington University in St. Louis Saint Louis MO USA

We propose a filtering method, called hierarchical particle filtering, for multi-modal sensor networks in which the unknown state vector is observed, through the measurements, in a hierarchical fashion. We partition the state space and the measurement space into lower dimensional subspaces. At each stage, we find an estimate of one partition using the measurements from the corresponding partition, and the information from the previous stages. We use hierarchical particle filtering for joint initiation, termination and tracking of multiple targets using multi-modal measurements. Numerical simulations demonstrate that the proposed filtering method accurately identifies the number and the categories of targets, and produces a lower mean-squared error (MSE) compared to the MSE obtained using a standard particle filter.

关键词： Target tracking Vectors Atmospheric measurements Particle measurements Cameras Multimodal sensors Standards

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4th workshop on Real-World Wireless sensor Networks, REALWSN 2010

4th Workshop on Real-World Wireless Sensor Networks, REALWSN...

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4th workshop on Real-World Wireless sensor Networks, REALWSN 2010

ISBN: (纸本)9783642175190

the proceedings contain 26 papers. the special focus in this conference is on Real-World Wireless sensor Networks. the topics include: Evaluation of an electronically switched directional antenna for real-world low-power wireless networks;implementation and evaluation of combined positioning and communication;SPIDA: A direction-finding antenna for wireless sensor networks;testing selective transmission with low power listening;An experimental study on ieee 802.15.4 multichannel transmission to improve RSSI–Based service performance;multicasting enabled routing protocol optimized for wireless sensor networks;GINSENG - Performance control in wireless sensor networks;lynxNet: Wild animal monitoring using sensor networks;demo abstract: Bridging the Gap between simulated sensor nodes and the real world;TigerCENSE: Wireless image sensor network to monitor tiger movement;a mote-in-the-loop approach for exploring communication strategies for sensor networks;the deployment of TikiriDB for monitoring palm sap production;cooperative virtual memory for sensor nodes;ginConf: A configuration and execution interface for wireless sensor network in industrial context;ediMote: A flexible sensor node prototyping and profiling tool;Virtual sensor WPAN on demand;TikiriAC: Node-level equally distributed access control for shared sensor networks;Motes in the jungle: Lessons learned from a short-term WSN deployment in the Ecuador cloud forest;deploying wireless sensor networking technology in a rescue team context;visibility levels: Managing the tradeoff between visibility and resource consumption;Flexible online energy accounting in tinyOS;TikiriDev: A UNIX-Like device abstraction for contiki;location based wireless sensor services in life science automation;hallway monitoring: Distributed data processing with wireless sensor networks.

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PROJECTION BACK ONTO FILTERED OBSERVATIONS FOR SPEECH SEPARATION WIth DISTRIBUTED MICROPHONE array 8

PROJECTION BACK ONTO FILTERED OBSERVATIONS FOR SPEECH SEPARA...

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8th ieee International workshop on Computational Advances in Multi-sensor Adaptive processing (CAMSAP)

作者： Araki, Shoko Ono, Nobutaka Kinoshita, Keisuke Delcroix, Marc NTT Corp NTT Commun Sci Labs 2-4 HikaridaiSeika Cho Kyoto 6190237 Japan Tokyo Metropolitan Univ Fac Syst Design 6-6 Asahigaoka Hino Tokyo 1910065 Japan

ISBN: (纸本)9781728155494

Many speech enhancement approaches generally estimate a source image on a reference microphone. For example, blind source separation approaches including independent vector analysis (IVA) usually determine the scales of the separated signals by using the projection back onto an observed signal at a reference microphone. However, when using distributed microphones, performance strongly depends on the selection of the reference microphone. therefore, a reference microphone selection strategy or a speech enhancement method that does not depend on the reference microphone is required. Previously, [Araki et al., IWAENC2018, pp. 316-320, 2018] proposed a blind reference microphone selection strategy. In this paper, we propose a new projection back method that does not depend on the reference microphone. Instead of projecting back onto a reference microphone observation, this paper proposes projecting back onto beamformed observed signals. We also show an equivalent system that can easily realize the proposed projection back approach practically. Experiments with real recordings of meeting conversations show that the proposed projection back approach outperforms conventional projection back approaches.

关键词： Distributed microphone reference microphone selection independent vector analysis projection back (back-projection) meeting recognition

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A subspace tracking algorithm for separating partially overlapping data packets

A subspace tracking algorithm for separating partially overl...

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sensor array and multichannel signal processing workshop

作者： Mu Zhou Alle-Jan van der Veen Department of Electrical Engineering Delft University of Technology Delft Netherlands

Consider a narrowband wireless scenario where a terminal equipped with an antenna array is receiving short packets of equal length sent by users from different directions and transmitted at random time points. these packets can be fully or partially overlapping in time. the partially overlapping packets, called asynchronous interferences, make the scenario nonstationary and thus need to be suppressed. Previously, we proposed a subspace intersection algorithm based on signed URV decompositions (SURV) working on block data from one time slot to solve this problem but it needs many steps. In this paper, we propose a one-step subspace tracking algorithm providing competitive performance at a much lower computational complexity like updating a QR decomposition. this algorithm makes use of the tracking ability of SURV to track the orthonormal basis and the rank of the asynchronous interference-free subspace as its principal subspace tracking version through two subspaces with positive and negative signatures.

关键词： Interference signal to noise ratio Silicon Vectors signal processing algorithms Indexes Radar tracking

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