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Improving Accuracy for 3D RFID Localization

INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2012年第unknown期2012卷 1-9页

作者： Han, Jinsong Zhao, Yiyang Cheng, Yan Shun Wong, Tse Lung Wong, Chun Hung Xi An Jiao Tong Univ Sch Elect & Informat Engn Xian 710049 Peoples R China Tsinghua Univ TNLIST Sch Software Beijing 100084 Peoples R China HKUST Dept Comp Sci & Engn Kowloon Hong Kong Peoples R China

Radio Frequency Identification (RFID) becomes a prevalent labeling and localizing technique in the recent years. Deploying indoor RFID localization systems facilitates many applications. Previous approaches, however, are most based on 2D design and cannot provide 3D location information. The lack of one-dimensional information may lead 2D-based systems to inaccurate localization. In this paper, we develop an indoor 3D RFID localization system based on active tag array. In particular, we employ the geometric mean to filter the explicit 3D location information with high accuracy. The experimental results show that our system is efficient in tracking objects and improving the localization accuracy.

关键词： ACCURACY of information RADIO frequency identification systems APPLICATION software COMPUTER engineering tracking algorithms LOCALIZATION theory

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Polynomial Chaos Theory for Performance Evaluation of ATR Systems

Polynomial Chaos Theory for Performance Evaluation of ATR Sy...

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Conference on Automatic Target Recognition XX - Acquisition, tracking, Pointing, and Laser Systems Technologies XXIV - and Optical Pattern Recognition XXI

作者： DeVore, Michael D. Bateman, Alec J. Barron Associates Inc Charlottesville VA USA

ISBN: (纸本)9780819481603

The development of a more unified theory of automatic target recognition (ATR) has received considerable attention over the last several years from individual researchers, working groups, and workshops. One of the major benefits expected to accrue from such a theory is an ability to analytically derive performance metrics that accurately predict real-world behavior. Numerous sources of uncertainty affect the actual performance of an ATR system, so direct calculation has been limited in practice to a few special cases because of the practical difficulties of manipulating arbitrary probability distributions over high dimensional spaces. This paper introduces an alternative approach for evaluating ATR performance based on a generalization of Norbert Wiener's polynomial chaos theory. Through this theory, random quantities are expressed not in terms of joint distribution functions but as convergent orthogonal series over a shared random basis. This form can be used to represent any finite-variance distribution and can greatly simplify the propagation of uncertainties through complex systems and algorithms. The paper presents an overview of the relevant theory and, as an example application, a discussion of how it can be applied to model the distribution of position errors from target tracking algorithms.

关键词： generalized polynomial chaos performance prediction ATR theory tracking algorithms

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Bayesian Approach to Extended Object and Cluster tracking using Random Matrices

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2008年第3期44卷 1042-1059页

作者： Koch, Johann Wolfgang FGAN FKIE D-53343 Wachtberg Germany

In algorithms for tracking and sensor data fusion the targets to be observed are usually considered as point source objects;i.e., compared with the sensor resolution their extension is neglected. Due to the increasing resolution capabilities of modem sensors, however, this assumption is often no longer valid as different scattering centers of an object can cause distinct detections when passing the signal processing chain. Examples of extended targets are found in short-range applications (littoral surveillance, autonomous weapons, or robotics). A collectively moving target group can also be considered as an extended target. This point of view is the more appropriate, the smaller the mutual distances between the individual targets are. Due to the resulting data association and resolution conflicts any attempt of tracking the individual objects within the group seems to be no longer reasonable. With simulated sensor data produced by a partly unresolvable aircraft formation the addressed phenomena are illustrated and an approximate Bayesian solution to the resulting tracking problem is proposed. Ellipsoidal object extensions are modeled by random matrices, which are treated as additional state variables to be estimated or tracked. We expect that the resulting tracking algorithms are also relevant for tracking large, collectively moving target swarms.

关键词： Bayes methods filtering theory matrix algebra pattern clustering random processes sensor fusion tracking Bayes method cluster tracking object extension random matrix sensor data fusion tracking algorithms

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A jump Markov particle filter for localization of moving terminals in multipath indoor scenarios

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2008年第8期56卷 3801-3809页

作者： Nicoli, M. Morelli, C. Rampa, V. Politecn Milan Dipartimento Elettron & Informaz I-20133 Milan Italy Nokia Siemens Networks SpA I-20060 Milan Italy Informat & Telecommun Engn Natl Res Council IEIIT Inst Elect I-20133 Milan Italy

This correspondence describes an efficient Bayesian framework for localization of moving terminals (MTs) in wideband wireless networks. In a previous paper, the authors have presented a grid-based technique, based on a hidden Markov model, that used the power delay profiles of the received signals to track the MT position. This grid-based Bayesian method has proved its efficacy in reducing localization errors in realistic indoor environments with multipath effects and mixed line-of-sight/non-line-of-sight (LOS/NLOS) conditions. However, the computational power and the memory storage requirements limit its use in practical wireless networks. To improve the computational efficiency, here we propose a jump-Markov particle-filter approach as an extension of the previous work;the LOS/NLOS sight process is the jumping feature that drives the MT motion dynamics, while the particle filter is used to track the MT position. Performance analyses, carried out for realistic multipath indoor environments, show that, with respect to the previous grid-based algorithm, this novel approach greatly reduces the tracking filter complexity still preserving the same localization accuracy. Simulation results prove also the robustness of the proposed method with respect to the uncertainty of sight statistics information.

关键词： Bayesian estimation hidden Markov model mobile positioning particle filter source localization tracking algorithms ultra-wideband communications

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Development and evaluation of a seismic monitoring system for building interiors - Part II: Image data analysis and results

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2008年第2期57卷 345-354页

作者： Doerr, Kai-Uwe Kuester, Falko Nastase, Derek Hutchinson, Tara C. Univ Calif San Diego Calif Inst Telecommun & Informat Technol La Jolla CA 92093 USA Univ Calif Irvine Dept Elect Engn & Comp Sci Irvine CA 92697 USA Univ Calif San Diego Dept Struct Engn La Jolla CA 92093 USA Univ Calif San Diego Dept Comp Sci & Engn La Jolla CA 92093 USA

Previous experiences during earthquake events emphasize the need for new technologies for real-time monitoring and assessment of facilities with high-value nonstructural contents. Moreover, there is a substantial limitation in our ability to rapidly evaluate and identify potential hazard zones within a structure, exposing rescue workers, society, and the environment to unnecessary risks. A real-time image-based monitoring system, which is integrated with warning systems, would allow for improved channeling of resources and informed decision making for rescue workers and building owners. In recognition of these issues, in this paper, we describe a methodology for image-based tracking of seismically induced motions. The methodology includes the acquisition, calibration, and processing of image sequences to detect and track object features under seismic-event conditions. We address the issue of providing a reliable feature/object-detection and object-tracking methodology for an image sequence from a single camera view. In addition, we introduce an extension to the 2-D tracking approach by providing a 3-D feature tracking methodology when the camera array itself is affected by the seismic event. The methods presented are demonstrated using the data collected during the full-scale field vibration tests conducted on a vacant building that was damaged during the 1994 Northridge Earthquake (presented in a companion paper). We present experimental tracking results of the implemented algorithms for a variety of objects and discuss additional challenges that emerge when image-based systems are used under these extreme conditions.

关键词： data acquisition field monitoring image acquisition image processing seismic motions synchronization tracking algorithms

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The ATLAS Experiment at the CERN Large Hadron Collider

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JOURNAL OF INSTRUMENTATION 2008年第08期3卷 S08003-S08003页

作者： Aad, G. Abat, E. Abdallah, J. Abdelalim, A. A. Abdesselam, A. Abdinov, O. Abi, B. A. Abolins, M. Abramowicz, H. Acerbi, E. Acharya, B. S. Achenbach, R. Ackers, M. Adams, D. L. Adamyan, F. Addy, T. N. Aderholz, M. Adorisio, C. Adragna, P. Aharrouche, M. Ahlen, S. P. Ahles, F. Ahmad, A. Ahmed, H. Aielli, G. Akesson, P. F. Akesson, T. P. A. Alam, S. M. Albert, J. Albrand, S. Aleksa, M. Aleksandrov, I. N. Aleppo, M. Alessandria, F. Alexa, C. Alexander, G. Alexopoulos, T. Alimonti, G. Aliyev, M. Allport, P. P. Allwood-Spiers, S. E. Aloisio, A. Alonso, J. Alves, R. Alviggi, M. G. Amako, K. Amaral, P. Amaral, S. P. Ambrosini, G. Ambrosio, G. Amelung, C. Ammosov, V. V. Amorim, A. Amram, N. Anastopoulos, C. Anderson, B. Anderson, K. J. Anderssen, E. C. Andreazza, A. Andrei, V. Andricek, L. Andrieux, M-L. Anduaga, X. S. Anghinolfi, F. Antonaki, A. Antonelli, M. Antonelli, S. Apsimon, R. Arabidze, G. Aracena, I. Arai, Y. Arce, A. T. H. Archambault, J. P. Arguin, J-F Arik, E. Arik, M. Arms, K. E. Armstrong, S. R. Arnaud, M. Arnault, C. Artamonov, A. Asai, S. Ask, S. Asman, B. Asner, D. Asquith, L. Assamagan, K. Astbury, A. Athar, B. Atkinson, T. Aubert, B. Auerbach, B. Auge, E. Augsten, K. Aulchenko, V. M. Austin, N. Avolio, G. Avramidou, R. Axen, A. Ay, C. Azuelos, G. Baccaglioni, G. Bacci, C. Bachacou, H. Bachas, K. Bachy, G. Badescu, E. Bagnaia, P. Bailey, D. C. Baines, J. T. Baker, O. K. Ballester, F. Pedrosa, F. Baltasar Dos Santos Banas, E. Banfi, D. Bangert, A. Bansal, V. Baranov, S. P. Baranov, S. Barashkou, A. Barberio, E. L. Barberis, D. Barbier, G. Barclay, P. Bardin, D. Y. Bargassa, P. Barillari, T. Barisonzi, M. Barnett, B. M. Barnett, R. M. Baron, S. Baroncelli, A. Barone, M. Barr, A. J. Barreiro, F. da Costa, J. Barreiro Guimaraes Barrillon, P. Poy, A. Barriuso Barros, N. Bartheld, V. Bartko, H. Bartoldus, R. Basiladze, S. Bastos, J. Batchelor, L. E. Bates, R. L. Batley, J. R. Batraneanu, S. Battistin, M. Battistoni, G. Batusov, V. Bauer, F. Bauss, B. Baynham, D. E. Bazalova, M. Bazan, A. Beauchemin, P. H. Bea CERN CH-1211 Geneva 23 Switzerland Univ Alberta Albany NY 12222 USA Univ Alberta Dept Phys Ctr Particle Phys Edmonton AB T6G 2G7 Canada Fac Sci Dept Phys TR-061000 Ankara Turkey Azerbaijan Acad Sci Inst Phys AZ-143 Baku Azerbaijan Univ Autonoma Barcelona Inst Fis Altes Energies ES-08193 Barcelona Spain Univ Belgrade Inst Phys Belgrade 11001 Serbia Univ Bergen Dept Phys & Technol NO-5007 Bergen Norway Univ Calif Berkeley Lawrence Berkeley Lab Berkeley CA 94720 USA Univ Calif Berkeley Div Phys Berkeley CA 94720 USA Humboldt Univ Inst Phys D-12489 Berlin Germany Univ Bern High Energy Phys Lab CH-3012 Bern Switzerland Univ Birmingham Sch Phys & Astron Birmingham B15 2TT W Midlands England Bogazici Univ Dept Phys Fac Sci TR-80815 Bebek Turkey Ist Nazl Fis Nucl IT-40127 Bologna Italy Univ Bologna Dipartimento Fis IT-40127 Bologna Italy Univ Bonn Inst Phys D-53115 Bonn Germany Boston Univ Dept Phys Boston MA 02215 USA Brandeis Univ Dept Phys Waltham MA 02454 USA Brookhaven Natl Lab Dept Phys Upton NY 11973 USA Natl Inst Phys & Nucl Engn R-077125 Bucharest Romania Univ Buenos Aires FCEyN Dept Fis RA-1428 Buenos Aires DF Argentina Univ Cambridge Cavendish Lab Cambridge CB3 OHE England Carleton Univ Dept Phys Ottawa ON K1S 5B6 Canada Univ Chicago Enrico Fermi Inst Chicago IL 60637 USA Pontificia Univ Catolica Chile Fac Fis Dept Fis Santiago 22 Chile Univ Tecn Federico Santa Maria Dept Fis Valparaiso Chile Chinese Acad Sci Inst HEP CN-100049 Beijing Peoples R China USTC Dept Modern Phys CN-230026 Hefei Anhui Peoples R China Nanjing Univ Dept Phys CN-210093 Nanjing Peoples R China Shandong Univ HEP Grp CN-250100 Shadong Peoples R China Univ Blaise Pascal CNRS IN2P3 Phys Corpusculaire Lab FR-63177 Aubiere France Columbia Univ Nevis Lab Irvington NY 10533 USA Univ Copenhagen Niels Bohr Inst DK-2100 Copenhagen O Denmark Ist Nazl Fis Nucl Grp Collegato Cosenza IT-87036 Arcavacata Di Rende Italy Univ Calabria Dipartime

The ATLAS detector as installed in its experimental cavern at point 1 at CERN is described in this paper. A brief overview of the expected performance of the detector when the Large Hadron Collider begins operation is... 详细信息

关键词： ATLAS LHC CERN Accelerator Proton-proton collisions Heavy-ion collisions Minimum-bias events Bunch-crossings Pile-up Superconducting magnets Solenoidal field Toroidal field Magnetic field measurements Hall probes Inner detector Charged-particle tracking Vertex measurement Pixel detectors Silicon micro-strip detectors Transition radiation Time-over-threshold Radiation-hard electronics Fluorinert cooling Carbon-fibre reinforced plastics Optical fibres Calorimetry Sampling calorimeters Liquid argon Scintillator tiles Electromagnetic and hadronic interactions Forward calorimetry Accordion geometry Lateral segmentation Longitudinal segmentation Muon spectrometer Precision-tracking chambers Trigger chambers Drift tubes Thin-gap chambers Resistive-plate chambers Optical alignment systems Forward detectors Cerenkov light Roman Pots Zero-degree calorimetry Trigger and data acquisition High-level trigger Event filter Detector control system Bandwidth Processor farm Electrons Muons Leptons Photons Jets Taus Missing transverse energy b-tagging Particle identification tracking algorithms Vertexing algorithms Impact parameter measurements

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A mathematical model for localization and tracking of telemetry. Capsules using RSSI signals

A mathematical model for localization and tracking of teleme...

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Conference on Bioengineered and Bioinspired Systems III

作者： Arshak, Khalil Adepoju, Francis Univ Limerick Dept Elect & Comp Engn Limerick Ireland

ISBN: (纸本)9780819467201

In this paper we consider the problem of tracking the real-time positions of a diagnostic capsule in the gastrointestinal (GI) tract. Our solution is. a fully developed estimation algorithm that utilizes radio frequency signals converted to voltage on the received signal strength indicator (RSSI) output of an array of transceivers. We employed a modified form of the traditional radio-map based deterministic model that requires an estimate of initial position vector. Data capture was implemented with commercial off-the shelf transceivers featuring RSSI outputs. At the intermediate processing stages, trilateration was employed as a mathematical tool to determine the approximate 2-D coordinates of unknown capsule locations by linearizing the resulting equations. This approach facilitates a PC-based implementation of fully automated real-time position measurements by eliminating the need to measure angles. In the final algorithm based on non linear least squares approximations, the Newton's iteration of the resulting Jacobian matrices were used to generate a more accurate position coordinates. Test Results from laboratory experiments demonstrate the accuracy of the solution in the centimeter range. This results in a position tracking measurements with an average value error of less than 25%. This kind of results guarantees that our solution can be adapted into telemetry capsules for use in diagnosing intestinal malfunctions.

关键词： RF signals telemetry capsule trilateration tracking algorithms and GI tract

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Simulation of manoeuvring target tracking algorithms using dynamic programming

Simulation of manoeuvring target tracking algorithms using d...

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12th IEEE-SPIE Symposium on Photonics and Web Engineering

作者： Holiczer, A Bialystok Tech Univ Dept Elect Engn PL-15351 Bialystok Poland

The present paper deals with simulation of tracking algorithms. Two target models are considered. All models are based on state equations using Newton matrices in the presence of Gaussian white noise. Simulated algori... 详细信息

ISBN: (纸本)081945415X

关键词： tracking algorithms Kalman filter estimation filter fault-tolerant system

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Hidden Markov models for radio localization in mixed LOS/NLOS conditions

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2007年第4期55卷 1525-1542页

作者： Morelli, Carlo Nicoli, Monica Rampa, Vittorio Spagnolini, Umberto Politecn Milan Dipartimento Elettr & Informat I-20133 Milan Italy CNR IEIIT CNR I-20133 Milan Italy

This paper deals with the problem of radio localization of moving terminals (MTs) for indoor applications with mixed line-of-sight/non-line-of-sight (LOS/NLOS) conditions. To reduce false localizations, a grid-based Bayesian approach is proposed to jointly track the sequence of the positions and the sight conditions of the MT. This method is based on the assumption that both the MT position and the sight condition are Markov chains whose state is hidden in the received signals [hidden Markov model (HMM)]. The observations used for the HMM localization are obtained from the power-delay profile of the received signals. In ultrawideband (UWB) systems, the use of the whole power-delay profile, rather than the total power only, allows to reach higher localization accuracy, as the power-profile is a joint measurement of time of arrival and power. Numerical results show that the proposed HMM method improves the accuracy of localization with respect to conventional ranging methods, especially in mixed LOS/NLOS indoor environments.

关键词： Bayesian estimation hidden Markov models (HMM) mobile positioning source localization tracking algorithms ultra-wideband (UWB) communications wireless networks

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Comments on Orphanides and Williams' "Robust monetary policy"

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JOURNAL OF MONETARY ECONOMICS 2007年第5期54卷 1436-1440页

作者： Bullard, James Fed Reserve Bank St Louis St Louis MO 63106 USA

关键词： learning and monetary policy lucas critique tracking algorithms expectational stability

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