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  • Presentation: 2017-03-29 10:15 Visionen, Hus B, Linköping
    Zhao, Yuxin
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Position Estimation in Uncertain Radio Environments and Trajectory Learning2017Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    To infer the hidden states from the noisy observations and make predictions based on a set of input states and output observations are two challenging problems in many research areas. Examples of applications many include position estimation from various measurable radio signals in indoor environments, self-navigation for autonomous cars, modeling and predicting of the traffic flows, and flow pattern analysis for crowds of people. In this thesis, we mainly use the Bayesian inference framework for position estimation in an indoor environment, where the radio propagation is uncertain. In Bayesian inference framework, it is usually hard to get analytical solutions. In such cases, we resort to Monte Carlo methods to solve the problem numerically. In addition, we apply Bayesian nonparametric modeling for trajectory learning in sport analytics.

    The main contribution of this thesis is to propose sequential Monte Carlo methods, namely particle filtering and smoothing, for a novel indoor positioning framework based on proximity reports. The experiment results have been further compared with theoretical bounds derived for this proximity based positioning system. To improve the performance, Bayesian non-parametric modeling, namely Gaussian process, has been applied to better indicate the radio propagation conditions. Then, the position estimates obtained sequentially using filtering and smoothing are further compared with a static solution, which is known as fingerprinting.

    Moreover, we propose a trajectory learning framework for flow estimation in sport analytics based on Gaussian processes. To mitigate the computation deficiency of Gaussian process, a grid-based on-line algorithm has been adopted for real-time applications. The resulting trajectory modeling for individual athlete can be used for many purposes, such as performance prediction and analysis, health condition monitoring, etc. Furthermore, we aim at modeling the flow of groups of athletes, which could be potentially used for flow pattern recognition, strategy planning, etc.

    List of papers
    1. Received-Signal-Strength Threshold Optimization Using Gaussian Processes
    Open this publication in new window or tab >>Received-Signal-Strength Threshold Optimization Using Gaussian Processes
    2017 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 65, no 8, 2164-2177 p.Article in journal (Refereed) Published
    Abstract [en]

    There is a big trend nowadays to use event-triggered proximity report for indoor positioning. This paper presents a generic received-signal-strength (RSS) threshold optimization framework for generating informative proximity reports. The proposed framework contains five main building blocks, namely the deployment information, RSS model, positioning metric selection, optimization process and management. Among others, we focus on Gaussian process regression (GPR)-based RSS models and positioning metric computation. The optimal RSS threshold is found through minimizing the best achievable localization root-mean-square-error formulated with the aid of fundamental lower bound analysis. Computational complexity is compared for different RSS models and different fundamental lower bounds. The resulting optimal RSS threshold enables enhanced performance of new fashioned low-cost and low-complex proximity report-based positioning algorithms. The proposed framework is validated with real measurements collected in an office area where bluetooth-low-energy (BLE) beacons are deployed.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2017
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-135065 (URN)10.1109/TSP.2017.2655480 (DOI)000395828700018 ()
    Projects
    TRAX
    Note

    Funding agencies: European Union FP7 Marie Curie training programme on Tracking in Complex Sensor Systems [607400]

    Available from: 2017-03-08 Created: 2017-03-08 Last updated: 2017-03-27Bibliographically approved
    2. Gaussian Process for Propagation modeling and Proximity Reports Based Indoor Positioning
    Open this publication in new window or tab >>Gaussian Process for Propagation modeling and Proximity Reports Based Indoor Positioning
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    2016 (English)In: 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring), IEEE , 2016, 1-5 p.Conference paper (Refereed)
    Abstract [en]

    The commercial interest in proximity services is increasing. Application examples include location-based information and advertisements, logistics, social networking, file sharing, etc. In this paper, we consider network-based positioning based on times series of proximity reports from a mobile device, either only a proximity indicator, or a vector of RSS from observed nodes. Such positioning corresponds to a latent and nonlinear observation model. To address these problems, we combine two powerful tools, namely particle filtering and Gaussian process regression (GPR) for radio signal propagation modeling. The latter also provides some insights into the spatial correlation of the radio propagation in the considered area. Radio propagation modeling and positioning performance are evaluated in a typical office area with Bluetooth-Low-Energy (BLE) beacons deployed for proximity detection and reports. Results show that the positioning accuracy can be improved by using GPR.

    Place, publisher, year, edition, pages
    IEEE, 2016
    National Category
    Communication Systems
    Identifiers
    urn:nbn:se:liu:diva-128255 (URN)10.1109/VTCSpring.2016.7504255 (DOI)000386528400206 ()9781509016983 (ISBN)
    Conference
    2016 IEEE 83rd Vehicular Technology Conference: VTC2016-Spring, 15–18 May 2016, Nanjing, China
    Available from: 2016-05-24 Created: 2016-05-24 Last updated: 2017-03-14Bibliographically approved
    3. Gaussian Processes for Flow Modeling and Prediction of Positioned Trajectories Evaluated with Sports Data
    Open this publication in new window or tab >>Gaussian Processes for Flow Modeling and Prediction of Positioned Trajectories Evaluated with Sports Data
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    2016 (English)In: 19th International Conference on  Information Fusion (FUSION), 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, 1461-1468 p.Conference paper (Refereed)
    Abstract [en]

    Kernel-based machine learning methods are gaining increasing interest in flow modeling and prediction in recent years. Gaussian process (GP) is one example of such kernelbased methods, which can provide very good performance for nonlinear problems. In this work, we apply GP regression to flow modeling and prediction of athletes in ski races, but the proposed framework can be generally applied to other use cases with device trajectories of positioned data. Some specific aspects can be addressed when the data is periodic, like in sports where the event is split up over multiple laps along a specific track. Flow models of both the individual skier and a cluster of skiers are derived and analyzed. Performance has been evaluated using data from the Falun Nordic World Ski Championships 2015, in particular the Men’s cross country 4 × 10 km relay. The results show that the flow models vary spatially for different skiers and clusters. We further demonstrate that GP regression provides powerful and accurate models for flow prediction.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2016
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering Probability Theory and Statistics
    Identifiers
    urn:nbn:se:liu:diva-129758 (URN)9780996452748 (ISBN)9781509020126 (ISBN)
    Conference
    19th International Conference on Information Fusion, 5-8 July 2016, Heidelberg, Germany
    Available from: 2016-06-27 Created: 2016-06-27 Last updated: 2017-03-14Bibliographically approved
  • Presentation: 2017-04-05 13:15 Alan Turing, Linköping
    Löfwenmark, Andreas
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering. Saab Aeronautics.
    Timing Predictability in Future Multi-Core Avionics Systems2017Licentiate thesis, monograph (Other academic)
    Abstract [en]

    With more functionality added to safety-critical avionics systems, new platforms are required to offer the computational capacity needed. Multi-core platforms offer a potential that is now being explored, but they pose significant challenges with respect to predictability due to shared resources (such as memory) being accessed from several cores in parallel. Multi-core processors also suffer from higher sensitivity to permanent and transient faults due to shrinking transistor sizes.

    This thesis addresses several of these challenges. First, we review major contributions that assess the impact of fault tolerance on worst-case execution time of processes running on a multi-core platform. In particular, works that evaluate the timing effects using fault injection methods. We conclude that there are few works that address the intricate timing effects that appear when inter-core interferences due to simultaneous accesses of shared resources are combined with the fault tolerance techniques. We assess the applicability of the methods to COTS multi-core processors used in avionics. We identify dark spots on the research map of the joint problem of hardware reliability and timing predictability for multi-core avionics systems.

    Next, we argue that the memory requests issued by the real-time operating systems (RTOS) must be considered in resource-monitoring systems to ensure proper execution on all cores.

    We also adapt and extend an existing method for worst-case response time analysis to fulfill the specific requirements of avionics systems. We relax the requirement of private memory banks to also allow cores to share memory banks.

  • Presentation: 2017-04-07 10:15 Planck, Fysikhuset, Linköping
    Lundén, Hampus
    Linköping University, Department of Physics, Chemistry and Biology, Applied Optics . Linköping University, Faculty of Science & Engineering. Swedish Defence Research Agency FOI, Electrooptical Systems.
    Sol-Gel Glasses Doped with Pt-Acetylides and Gold Nanoparticles for Enhanced Optical Power Limiting2017Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    High power laser pulses can be a threat to sensors, including the human eye. Traditionally this threat has been alleviated by colour filters that blocks radiation in chosen wavelength ranges. Colour filters’ main drawback is that they block radiation regardless of it being useful or damaging, information is removed for wavelengths at which the filter protect. Protecting the entire wavelength range of a sensor would block or strongly attenuate the radiation needed for the operation of the sensor.

    Sol-gel glasses highly doped with Pt-Acetylide chromophores have previously shown high optical quality in combination with efficient optical power limiting through reverse saturable absorption1. These filters will transmit visible light unless the light fluence is above a certain threshold. A key design consideration of laser protection filters is linear absorption in relation to threshold level. By increasing chromophore concentration the threshold is lowered at the expense of higher linear absorption. This means that the user’s view is degraded through the filter.

    Adding small amounts of gold nanoparticles to the glasses resulted in an increase in optical power limiting performance. The optimal concentration of gold nanoparticles corresponded to a mean particle distance of several micrometers. The work in this licentiate thesis is about the characterization and explanation of this effect.

    The glasses investigated in this work were MTEOS Sol-Gel glasses doped with either only gold nanoparticles of varying shape and concentration, 50mM of PE2-CH2OH codoped with gold nanoparticles or 50mM of PE3-CH2OH codoped with gold nanoparticles. The glasses only doped with gold nanoparticles showed high optical power limiting performance at 532nm laser wavelength, but no optical power limiting at the fluences tested at 600nm. The PE2-CH2OH glasses codoped with gold nanoparticles showed an enhancement of optical power limiting at 600nm for the low gold nanoparticle concentration glasses. The enhancement was weakened or not present for higher concentrations. A similar enhancement above noise level for the PE3-CH2OH glasses was not found.

    A population model is used to give a qualitative explanation of the findings. The improvement in optical power limiting performance for the PE2-CH2OH glasses is explained by the gold nanoparticles helping to more quickly populate the highly absorbing triplet state during the rising edge of the laser pulse by enhancing two-photon absorption. The lack of any marked enhancement for the PE3-CH2OH glasses is explained by the PE3-CH2OH chromophore already being of sufficiently high performance to quickly populate the highly absorbing triplet state during the rising edge of the laser pulse. Further work is necessary to validate this model against other chromophores and improving its quantitative predictive power.

    List of papers
    1. Dispersion and self-orientation of gold nanoparticles in sol-gel hybrid silica - optical transmission properties
    Open this publication in new window or tab >>Dispersion and self-orientation of gold nanoparticles in sol-gel hybrid silica - optical transmission properties
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    2015 (English)In: Journal of Materials Chemistry C, ISSN 2050-7526, Vol. 3, no 5, 1026-1034 p.Article in journal (Refereed) Published
    Abstract [en]

    Silica-based hybrid materials doped with gold nanoparticles (AuNPs) of different shapes were prepared with an adapted sol-gel technology (using MTEOS) and polished to high optical quality. Both spherical (23 and 45 nm in diameter) and bipyramidal (36, 50 and 78 nm in length) AuNPs were prepared and used as dopants. The AuNPs were functionalized with a novel silicone polymer for compatibilization with the sol-gel medium. The glass materials showed well defined localized surface plasmon resonance (SPR) absorbance from the visible to NIR. No redshifts in the spectra, due to the increase in doping concentration, were observed in the glasses, proving that no or very small SPR coupling effects occur. Spectroscopic Muller Matrix Ellipsometry showed that the shorter bipyramidal AuNPs (36 and 50 nm in length) have a clear preferred orientation in the MTEOS matrix, i.e. a tendency to be oriented with their long axis in the plane parallel to the glass surfaces. Dispersions of AuNPs have proven to be good optical power limiters that depend on particle size and geometry. The solid-state glass materials showed good optical power limiting at 532 nm for nanosecond pulses, which did not depend on the size or geometry of the AuNPs. In contrast to the observation at 532 nm, at 600 nm no optical limiting effect was observed. In these solids, as for dispersions of AuNPs, the optical limiting response is caused by scattering.

    Place, publisher, year, edition, pages
    Royal Society of Chemistry, 2015
    National Category
    Physical Chemistry
    Identifiers
    urn:nbn:se:liu:diva-114589 (URN)10.1039/c4tc02353f (DOI)000348300300017 ()
    Note

    Funding Agencies|Swedish Armed Forces; EOARD [FA8655-12-12106]; AFRL [FA8655-12-12106]

    Available from: 2015-02-27 Created: 2015-02-26 Last updated: 2017-03-16
    2. Long Distance Enhancement of Nonlinear Optical Properties Using Low Concentration of Plasmonic Nanostructures in Dye Doped Monolithic Sol-Gel Materials.
    Open this publication in new window or tab >>Long Distance Enhancement of Nonlinear Optical Properties Using Low Concentration of Plasmonic Nanostructures in Dye Doped Monolithic Sol-Gel Materials.
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    2016 (English)In: Advanced Functional Materials, ISSN 1616-301X, E-ISSN 1616-3028, Vol. 26, no 33, 10 p.Article in journal (Refereed) Published
    Abstract [en]

    Monolithic sol-gel silica composites incorporating platinum-based chromophores and various types of gold nanoparticles (AuNPs) are prepared and polished to high optical quality. Their photophysical properties are investigated. The glass materials show well-defined localized surface plasmon resonance (SPR) absorbance from the visible to NIR. No redshifts of the AuNP plasmon absorption peaks due to the increase in nanoparticle doping concentration are observed in the glasses, proving that no or very small SPR coupling effects occur between the AuNPs. At 600 nm excitation, but not at 532 nm, the AuNPs improve the nonlinear absorption performance of glasses codoped with 50 × 10−3 m of a Pt-acetylide chromophore. The glasses doped with lower concentrations of AuNPs (2-5 μm average distance) and 50 × 10−3 m in chromophore, show a marked improvement in nonlinear absorption, with no or only small improvement for the more highly AuNP doped glasses. This study shows the importance of excitation wavelength and nanoparticle concentration for composite systems employing AuNPs to improve two-photon absorption of chromophores. [ABSTRACT FROM AUTHOR]

    Place, publisher, year, edition, pages
    Weinheim: , 2016. 10 p.
    Keyword
    hybrid material, nonlinear absorption, nonlinear optics, plasmon, sol-gel
    National Category
    Atom and Molecular Physics and Optics
    Identifiers
    urn:nbn:se:liu:diva-135513 (URN)10.1002/adfm.201601646 (DOI)
    Available from: 2017-03-16 Created: 2017-03-16 Last updated: 2017-03-16Bibliographically approved