300 research outputs found

    On the Application of the Baum-Welch Algorithm for Modeling the Land Mobile Satellite Channel

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    Accurate channel models are of high importance for the design of upcoming mobile satellite systems. Nowadays most of the models for the LMSC are based on Markov chains and rely on measurement data, rather than on pure theoretical considerations. A key problem lies in the determination of the model parameters out of the observed data. In this work we face the issue of state identification of the underlying Markov model whose model parameters are a priori unknown. This can be seen as a HMM problem. For finding the ML estimates of such model parameters the BW algorithm is adapted to the context of channel modeling. Numerical results on test data sequences reveal the capabilities of the proposed algorithm. Results on real measurement data are finally presented.Comment: IEEE Globecom 201

    Modeling of the Land Mobile Satellite Channel considering the Terminal’s Driving Direction

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    A precise characterization of the Land Mobile Satellite (LMS) channel, that is, the channel between a satellite and a mobile terminal, is of crucial importance while designing a satellite-based communication system. State-of-the-art statistical LMS channel models offer the advantage of requiring only a few input parameters, which include the environment type and the elevation angle of the satellite. However, the azimuth angle relative to the driving direction of the mobile terminal is usually ignored, as its proper modeling requires either an extensive measurement campaign or a significant effort from the user, as a precise geometrical description of the scenario is required. In this contribution we show that the impact of the driving direction on the channel statistics is not negligible and requires to be modeled explicitly. Moreover, we propose a statistical LMS channel model whose parameters are obtained via an image-based state estimation method. The image-based method is verified by a comparison with measured radio frequency signal levels. The proposed method allows obtaining a complete statistical description of the channel for arbitrary elevation and azimuth angles

    On the use of autonomous unmanned vehicles in response to hazardous atmospheric release incidents

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    Recent events have induced a surge of interest in the methods of response to releases of hazardous materials or gases into the atmosphere. In the last decade there has been particular interest in mapping and quantifying emissions for regulatory purposes, emergency response, and environmental monitoring. Examples include: responding to events such as gas leaks, nuclear accidents or chemical, biological or radiological (CBR) accidents or attacks, and even exploring sources of methane emissions on the planet Mars. This thesis presents a review of the potential responses to hazardous releases, which includes source localisation, boundary tracking, mapping and source term estimation. [Continues.]</div

    Rich probabilistic models for semantic labeling

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    Das Ziel dieser Monographie ist es die Methoden und Anwendungen des semantischen Labelings zu erforschen. Unsere BeitrÀge zu diesem sich rasch entwickelten Thema sind bestimmte Aspekte der Modellierung und der Inferenz in probabilistischen Modellen und ihre Anwendungen in den interdisziplinÀren Bereichen der Computer Vision sowie medizinischer Bildverarbeitung und Fernerkundung

    Development of Real-Time Surface Water Abstraction Management Tools

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    Efficient use of available water resources to meet demand, whilst maintaining the quality of the aquatic environment has become increasingly important. Water quality challenges associated with diffuse agricultural pollutions have also become widely recognized problems globally. This thesis presents the development of new approaches to improve surface water abstraction management with a view to mitigate the challenges associated with increasing pressures on availability of water resources for public water supply and diffuse agricultural pollution. The first part of the thesis presents the development of a real-time surface water abstraction management scheme that integrates a conceptual rainfall-runoff model, a Bayesian inference based uncertainty analysis tool and a water resources management model that incorporates various operating rules to represent real-world operational constraints. The developed approach enables efficient utilization of available water resources and thus provides improved capability to deal with emerging issues of increasing demand, climate adaptation planning and associated policy reforms. The second part of the thesis describes the development of a new travel time based physically distributed metaldehyde prediction model, which enables water infrastructure operators to consider informed surface water abstraction decisions. Metaldehyde is a soluble synthetic aldehyde pesticide used globally in agriculture and has caused recent concerns due to high observed levels in surface waters utilized for potable water supply. The model provides new approach to represent spatially and temporally disaggregated runoff generation, routing and build-up/wash-off processes using a grid based structure in a GIS environment. Furthermore, a state-of-the-art Monte Carlo based spatial uncertainty analysis tool is employed to assess uncertainties in the metaldehyde prediction model. The structure of the metaldehyde model combined with the availability of high spatiotemporal resolution data has enabled the application of spatial uncertainty analysis of the catchment scale metaldehyde model, which is currently lacking in water quality modelling studies

    Modeling and Analysis of Stochastic Radio Channels:An Application of the Theory of Spatial Point Processes

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    On Channel Modelling for Land Mobile Satellite Reception

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    ï»żIn modernen Satellitenrundfunksystemen werden Methoden wie ZeitdiversitĂ€t (Empfang von zeitlich verteilter Information) und WinkeldiversitĂ€t (Empfang von mehreren Satelliten mit unterschiedlichen Positionen) angewandt, um die geforderte DienstequalitĂ€t fĂŒr den mobilen Empfang zu gewĂ€hrleisten. Zur Untersuchung der Ausbreitungseffekte des landmobilen Satellitenkanals sowohl der Wirksamkeit von DiversitĂ€t werden statistische Modelle benötigt, die den zeitlichen Signalschwund des Empfangssignals nachbilden. In der vorliegenden Arbeit wird ein Kanalmodell fĂŒr den Mehrsatellitenempfang entwickelt, welches genaue Versorgungsvorhersagen mit Zeit- und WinkeldiversitĂ€t erlaubt.Grundlage ist ein Einsatellitenmodell, welches großrĂ€umige Schwankungen im Kanal durchdie ZustĂ€nde ’gut’ und ’schlecht’ definiert, und den langsamen und schnellen Signalschwund gemĂ€ĂŸ einer variablen Loo-Verteilung beschreibt, deren Parameter nach jedem Zustandswechsel stochastisch bestimmt werden. FĂŒr die Zustandsmodellierung mit zwei Satelliten wird ein 'semi-Markov Modell fĂŒr korrellierte Zustandssequenzen' erarbeitet. Damit können, unter BerĂŒcksichtigung der Statistiken der EinzelkanĂ€le und deren Korrelationskoeffizient, die Zustandswahrscheinlichkeiten und-lĂ€ngen exakt simuliert werden. FĂŒr die Zustandsmodellierung mit drei Satelliten wird ein 'Master-Slave'-Ansatz entwickelt. Dabei sind die Zustandssequenzen zweier ’Slaves’ bedingt abhĂ€ngig zur ’Master’-Sequenz. Der ’Master-Slave’-Ansatz ermöglicht die Parametrisierung eines Dreisatellitenmodells. Zur Beschreibung des langsamen und schnellen Signalschwunds im Mehrsatellitenkanal wirddie Wechselbeziehung zwischen synchron gemessenen Satellitensignalen nĂ€her untersucht.Es stellt sich heraus dass weitere Signalkorrelationen berĂŒcksichtigt werden sollten, dieerstmalig im neuen LMS-Kanalmodell implementiert werden. Die Simulationssergebnisse werden in Statistiken erster und zweiter Ordnung den Messdaten gegenĂŒbergestellt. Im Vergleich zu bestehenden Modellen werden Verbesserungen nach BerĂŒcksichtigung von DiversitĂ€t deutlich. Die Parameter fĂŒr das Mehrsatellitenkanalmodell wurden aus umfassenden Messkampagnen abgeleitet und gewĂ€hrleisten die Signalsimulation fĂŒr verschiedene Umgebungen und Satellitenpositionen. Abschließend wird das Kanalmodell fĂŒr einen ersten Vergleich verschiedener Satellitenkonfigurationen mit Zeit- und WinkeldiversitĂ€t angewandt.Modern digital satellite broadcasting systems combine time diversity (i.e. information is spread over a certain time interval) with angle diversity (i.e. information is received from multiple satellites in different orbital positions) to ensure uninterrupted service for mobile receivers over large areas. For assessing propagation effects of the land mobile satellite (LMS) channel and to study the efficacy of diversity, statistical models are required which generate time series of the received fading signal. In this thesis a narrowband LMS channel model for multi-satellite reception is developed focusing on accurate coverage prediction under consideration of angle- and time diversity. Basis is an existing single-satellite model, which describes large-scale signal variations of the channel by 'good' and 'bad' states, and models slow- and fast signal variations according to a versatile Loo distribution, which parameters are selected randomly when the channel enters a new state. For dual-satellite state modelling, a semi-Markov model for correlated state sequences is developed. It provides an accurate state probability and state duration modelling by considering the statistics of separate channels and their correlation coefficient. For the state modelling with three satellites, a new Master-Slave concept is introduced. Therefore, state sequences of slave satellites are conditioned by an existing master state sequence. The great advantage is that Master-Slave makes the parametrisation of a triple-satellite model feasible. To address slow- and fast variations for multi-satellite reception, the fading interdependence between synchronously received satellite signals is analysed from high-resolution measurement data. Hence additional correlations besides the state correlation are identified and firstly considered in the new multi-satellite LMS model. The modelling results are compared with the measurements in terms of first- and second order statistics, where improvements in describing diversity become visible when compared to existing models. Model parameters are derived from large-scale measurement campaigns to enable a time series generation for different environments and various constellations of satellites. The applicability of the new model is finally demonstrated by comparing the performance of different satellite constellations with diversity

    On Channel Modelling for Land Mobile Satellite Reception

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    ï»żIn modernen Satellitenrundfunksystemen werden Methoden wie ZeitdiversitĂ€t (Empfang von zeitlich verteilter Information) und WinkeldiversitĂ€t (Empfang von mehreren Satelliten mit unterschiedlichen Positionen) angewandt, um die geforderte DienstequalitĂ€t fĂŒr den mobilen Empfang zu gewĂ€hrleisten. Zur Untersuchung der Ausbreitungseffekte des landmobilen Satellitenkanals sowohl der Wirksamkeit von DiversitĂ€t werden statistische Modelle benötigt, die den zeitlichen Signalschwund des Empfangssignals nachbilden. In der vorliegenden Arbeit wird ein Kanalmodell fĂŒr den Mehrsatellitenempfang entwickelt, welches genaue Versorgungsvorhersagen mit Zeit- und WinkeldiversitĂ€t erlaubt.Grundlage ist ein Einsatellitenmodell, welches großrĂ€umige Schwankungen im Kanal durchdie ZustĂ€nde ’gut’ und ’schlecht’ definiert, und den langsamen und schnellen Signalschwund gemĂ€ĂŸ einer variablen Loo-Verteilung beschreibt, deren Parameter nach jedem Zustandswechsel stochastisch bestimmt werden. FĂŒr die Zustandsmodellierung mit zwei Satelliten wird ein 'semi-Markov Modell fĂŒr korrellierte Zustandssequenzen' erarbeitet. Damit können, unter BerĂŒcksichtigung der Statistiken der EinzelkanĂ€le und deren Korrelationskoeffizient, die Zustandswahrscheinlichkeiten und-lĂ€ngen exakt simuliert werden. FĂŒr die Zustandsmodellierung mit drei Satelliten wird ein 'Master-Slave'-Ansatz entwickelt. Dabei sind die Zustandssequenzen zweier ’Slaves’ bedingt abhĂ€ngig zur ’Master’-Sequenz. Der ’Master-Slave’-Ansatz ermöglicht die Parametrisierung eines Dreisatellitenmodells. Zur Beschreibung des langsamen und schnellen Signalschwunds im Mehrsatellitenkanal wirddie Wechselbeziehung zwischen synchron gemessenen Satellitensignalen nĂ€her untersucht.Es stellt sich heraus dass weitere Signalkorrelationen berĂŒcksichtigt werden sollten, dieerstmalig im neuen LMS-Kanalmodell implementiert werden. Die Simulationssergebnisse werden in Statistiken erster und zweiter Ordnung den Messdaten gegenĂŒbergestellt. Im Vergleich zu bestehenden Modellen werden Verbesserungen nach BerĂŒcksichtigung von DiversitĂ€t deutlich. Die Parameter fĂŒr das Mehrsatellitenkanalmodell wurden aus umfassenden Messkampagnen abgeleitet und gewĂ€hrleisten die Signalsimulation fĂŒr verschiedene Umgebungen und Satellitenpositionen. Abschließend wird das Kanalmodell fĂŒr einen ersten Vergleich verschiedener Satellitenkonfigurationen mit Zeit- und WinkeldiversitĂ€t angewandt.Modern digital satellite broadcasting systems combine time diversity (i.e. information is spread over a certain time interval) with angle diversity (i.e. information is received from multiple satellites in different orbital positions) to ensure uninterrupted service for mobile receivers over large areas. For assessing propagation effects of the land mobile satellite (LMS) channel and to study the efficacy of diversity, statistical models are required which generate time series of the received fading signal. In this thesis a narrowband LMS channel model for multi-satellite reception is developed focusing on accurate coverage prediction under consideration of angle- and time diversity. Basis is an existing single-satellite model, which describes large-scale signal variations of the channel by 'good' and 'bad' states, and models slow- and fast signal variations according to a versatile Loo distribution, which parameters are selected randomly when the channel enters a new state. For dual-satellite state modelling, a semi-Markov model for correlated state sequences is developed. It provides an accurate state probability and state duration modelling by considering the statistics of separate channels and their correlation coefficient. For the state modelling with three satellites, a new Master-Slave concept is introduced. Therefore, state sequences of slave satellites are conditioned by an existing master state sequence. The great advantage is that Master-Slave makes the parametrisation of a triple-satellite model feasible. To address slow- and fast variations for multi-satellite reception, the fading interdependence between synchronously received satellite signals is analysed from high-resolution measurement data. Hence additional correlations besides the state correlation are identified and firstly considered in the new multi-satellite LMS model. The modelling results are compared with the measurements in terms of first- and second order statistics, where improvements in describing diversity become visible when compared to existing models. Model parameters are derived from large-scale measurement campaigns to enable a time series generation for different environments and various constellations of satellites. The applicability of the new model is finally demonstrated by comparing the performance of different satellite constellations with diversity
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