Dissertations / Theses on the topic 'Multiple systems estimation'
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1
Miao, H. (Honglei). "Channel estimation and positioning for multiple antenna systems." Doctoral thesis, University of Oulu, 2007. http://urn.fi/urn:isbn:9789514284113.
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Abstract
The multiple–input multiple–output (MIMO) technique, applying several transmit and receive antennas in wireless communications, has emerged as one of the most prominent technical breakthroughs of the last decade. Wideband MIMO parameter estimation and its applications to the MIMO orthogonal frequency division multiplexing (MIMO–OFDM) channel estimation and mobile positioning are studied in this thesis.
Two practical MIMO channel models, i.e., correlated-receive independent-transmit channel and correlated-transmit-receive channel, and associated space-time parameter estimation algorithms are considered. Thanks to the specified structure of the proposed training signals for multiple transmit antennas, the iterative quadrature maximum likelihood (IQML) algorithm is applied to estimate the time delay and spatial signature for the correlated-receive independent-transmit MIMO channels. For the correlated-transmit-receive MIMO channels, the spatial signature matrix corresponding to a time delay can be further decomposed in such a way that the angle of arrival (AOA) and the angle of departure (AOD) can be estimated simultaneously by the 2-D unitary ESPRIT algorithm. Therefore, the combination of the IQML algorithm and the 2-D unitary ESPRIT algorithm provides a novel solution to jointly estimate the time delay, the AOA and the AOD for the correlated-transmit-receive MIMO channels. It is demonstrated from the numerical examples that the proposed algorithms can obtain good performance at a reasonable cost.
Considering the correlated-receive independent-transmit MIMO channels, channel coefficient estimation for the MIMO–OFDM system is studied. Based on the parameters of the correlated-receive independent-transmit MIMO channels, the channel statistics in terms of the correlation matrix are developed. By virtue of the derived channel statistics, a joint spatial-temporal (JST) filtering based MMSE channel estimator is proposed which takes full advantage of the channel correlation properties. The mean square error (MSE) of the proposed channel estimator is analyzed, and its performance is also demonstrated by Monte Carlo computer simulations. It is shown that the proposed JST minimum mean square error (MMSE) channel estimator outperforms the more conventional temporal MMSE channel estimator in terms of the MSE when the signals in the receive antenna array elements are significantly correlated. The closed form bit error probability of the space-time block coded OFDM system with correlation at the receiver is also developed by taking the channel estimation errors and channel statistics, i.e., correlation at the receiver, into account.
Mobile positioning in the non-line of sight (NLOS) scenarios is studied. With the knowledge of the time delay, the AOA and the AOD associated with each NLOS propagation path, a novel geometric approach is proposed to calculate the MS's position by only exploiting two NLOS paths. On top of this, the least squares and the maximum likelihood (ML) algorithms are developed to utilize multiple NLOS paths to improve the positioning accuracy. Moreover, the ML algorithm is able to estimate the scatterers' positions as well as those of the MSs. The Cramer-Rao lower bound related to the position estimation in the NLOS scenarios is derived. It is shown both analytically and through computer simulations that the proposed algorithms are able to estimate the mobile position only by employing the NLOS paths.
2
Abd, El-Sallam Amar. "Low order channel estimation for CDMA systems." Thesis, Curtin University, 2005. http://hdl.handle.net/20.500.11937/2420.
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New approaches and algorithms are developed for the identification and estimation of low order models that represent multipath channel effects in Code Division Multiple Access (CDMA) communication systems. Based on these parsimonious channel models, low complexity receivers such as RAKE receivers are considered to exploit these propagation effects and enhance the system performance. We consider the scenario where multipath is frequency selective slowly fading and where the channel components including delays and attenuation coefficients are assumed to be constant over one or few signalling intervals. We model the channel as a long FIR-like filter (or a tapped delay line filter) with the number of taps related to the ratio between the channel delay-spread and the chip duration. Due to the high data rate of new CDMA systems, the channel length in terms of the chip duration will be very large. With classical channel estimation techniques this will result in poor estimates of many of the channel parameters where most of them are zero leading to a reduction in the system performance. Unlike classical techniques which estimate directly the channel response given the number of taps or given an estimate of the channel length, the proposed techniques in this work will firstly identify the significant multipath parameters using model selection techniques, then estimate these identified parameters. Statistical tests are proposed to determine whether or not each individual parameter is significant. A low complexity RAKE receiver is then considered based on estimates of these identified parameters only. The level of significance with which we will make this assertion will be controlled based on statistical tests such as multiple hypothesis tests. Frequency and time domain based approaches and model selection techniques are proposed to achieve the above proposed objectives.The frequency domain approach for parsimonious channel estimation results in an efficient implementation of RAKE receivers in DS-CDMA systems. In this approach, we consider a training based strategy and estimate the channel delays and attenuation using the averaged periodogram and modified time delay estimation techniques. We then use model selection techniques such as the sphericity test and multiple hypotheses tests based on F-Statistics to identify the model order and select the significant channel paths. Simulations show that for a pre-defined level of significance, the proposed technique correctly identifies the significant channel parameters and the parsimonious RAKE receiver shows improved statistical as well as computational performance over classical methods. The time domain approach is based on the Bootstrap which is appropriate for the case when the distribution of the test statistics required by the multiple hypothesis tests is unknown. In this approach we also use short training data and model the channel response as an FIR filter with unknown length. Model parameters are then estimated using low complexity algorithms in the time domain. Based on these estimates, bootstrap based multiple hypotheses tests are applied to identify the non-zero coefficients of the FIR filter. Simulation results demonstrate the power of this technique for RAKE receivers in unknown noise environments. Finally we propose adaptive blind channel estimation algorithms for CDMA systems. Using only the spreading code of the user of interest and the received data sequence, four different adaptive blind estimation algorithms are proposed to estimate the impulse response of frequency selective and frequency non-selective fading channels. Also the idea is based on minimum variance receiver techniques. Tracking of a frequency selective varying fading channel is also considered.A blind based hierarchical MDL model selection method is also proposed to select non-zero parameters of the channel response. Simulation results show that the proposed algorithms perform better than previously proposed algorithms. They have lower complexity and have a faster convergence rate. The proposed algorithms can also be applied to the design of adaptive blind channel estimation based RAKE receivers.
3
Kane, Roma. "Multiuser TDMA channel estimation." Diss., Columbia, Mo. : University of Missouri-Columbia, 2004. http://hdl.handle.net/10355/5810.
Full textAbstract:
Thesis (M.S.)--University of Missouri-Columbia, 2004.The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (June 30, 2006) Vita. Includes bibliographical references.
4
Baştürk, İlhan Özbek Berna. "Iterative Channel Estimation Techniques For Multiple İnput Multiple Output Orthogonal Frequency Division Multiplexing Systems/." [s.l.]: [s.n.], 2007. http://library.iyte.edu.tr/tezler/master/elektrikveelektronikmuh/T000653.pdf.
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5
Orguner, Umut. "Improved State Estimation For Jump Markov Linear Systems." Phd thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607895/index.pdf.
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This thesis presents a comprehensive example
framework on how current multiple model state estimation algorithms for jump Markov linear systems can be improved. The possible improvements are categorized as:
-Design of multiple model state estimation algorithms using
new criteria.
-Improvements obtained using existing multiple model state
estimation algorithms.
In the first category, risk-sensitive estimation is proposed for
jump Markov linear systems. Two types of cost functions namely, the instantaneous and cumulative cost functions related with risk-sensitive estimation are examined and for each one, the
corresponding multiple model estate estimation algorithm is derived.
For the cumulative cost function, the derivation involves the
reference probability method where one defines and uses a new
probability measure under which the involved processes has
independence properties. The performance of the proposed
risk-sensitive filters are illustrated and compared with
conventional algorithms using simulations.
The thesis addresses the second category of improvements by
proposing
-Two new online transition probability estimation schemes for
jump Markov linear systems.
-A mixed multiple model state estimation scheme which combines
desirable properties of two different multiple model state
estimation methods.
The two online transition probability estimators proposed use the
recursive Kullback-Leibler (RKL) procedure and the maximum
likelihood (ML) criteria to derive the corresponding identification
schemes. When used in state estimation, these methods result in an average error decrease in the root mean square (RMS) state
estimation errors, which is proved using simulation studies.
The mixed multiple model estimation procedure
which utilizes the analysis of the single Gaussian approximation of Gaussian mixtures in Bayesian filtering, combines IMM (Interacting Multiple Model) filter and GPB2 (2nd Order Generalized Pseudo Bayesian) filter efficiently. The resulting algorithm reaches the performance of GPB2 with less Kalman filters.
6
Sadough, Seyed Mohammad Sajad. "Ultra wideband OFDM systems : channel estimation and improved detection accounting for estimation inaccuracies." Paris 11, 2008. http://www.theses.fr/2008PA112001.
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Les travaux présentés dans cette thèse se situent dans le cadre de la transmission OFDM appliqué au contexte Ultra Large Bande (UWB). L’objectif principal va être l’estimation du canal de propagation et la conception de récepteurs en prenant en compte la connaissance non idéale du canal. On propose d’abord une approche semi-aveugle d’estimation du canal qui bénéficie de la parcimonie du canal UWB dans le domaine des ondelettes pour réduire le nombre de paramètre à estimer. Ensuite, on propose des structures de réception itérative où la conception du détecteur prend en compte la présence des erreurs d’estimation de canal. La détection au sens maximum de vraisemblance (MV) est améliorée en modifiant sa métrique de détection pour le cas où le canal est estimé de manière imparfaite. La métrique MV améliorée ainsi obtenue nous permet de remettre en question le schéma de détection de type turbo MAP dans un contexte BICM et l’adapter à la connaissance imparfaite du canal. De plus, on dérive les débits de coupure atteignables (achievable outage rates) avec le détecteur MV améliorée ou un détecteur MV désadapté (utilisant les estimés de canal comme s’il s’agissait des vraies) qu’on comparera avec un détecteur théorique défini comme étant le meilleur récepteur possible en présence d’erreurs d’estimation de canal. Enfin, un récepteur itératif à complexité réduite basé sur un filtrage MMSE et l’annulation parallèle d’interférence (turbo-PIC) est introduit et ensuite adapté à la connaissance imparfaite du canal. Il est important de souligner que les améliorations proposées dans cette thèse n’impliquent pas une augmentation sensible de la complexité au niveau du récepteurThe aim of this thesis is to study the problem of iterative data detection in an ultra wideband (UWB) OFDM system, where the receiver disposes only of an imperfect (and possibly poor) estimate of the unknown channel parameters. First, we propose an efficient receiver jointly estimating the channel and the transmitted symbols in an iterative manner. This receiver is based on a wavelet representation of the unknown channel and exploits the sparseness property of UWB channels in the wavelet domain to reduce the receiver’s computational complexity. Second, we rely on the statistics characterizing the quality of the channel estimation as a mean to integrate the imperfect channel knowledge into the design of iterative receivers. In this way, we formulate an improved maximum likelihood (ML) detection metric taking into account the presence of channel estimation errors. A modified iterative MAP detector is derived by an appropriate use of this metric. The results are compared to those obtained by using the classical mismatched ML detector, which uses the channel estimate as if it was the perfect channel. Furthermore, we calculate the achieved throughputs associated to both improved and mismatched ML detectors, in terms of achievable outage rates. Finally, we propose an improved low-complexity iterative detector based on soft parallel interference cancellation and linear MMSE filtering where we takes into account the presence of channel estimation errors in the formulation of the detector. The important point is that the performance improvements reported in this thesis are obtained while imposing practically no additional complexity to the receiver
7
Allen, Randal T. "Robust estimation and adaptive guidance for multiple UAVs' cooperation." Orlando, Fla. : University of Central Florida, 2009. http://purl.fcla.edu/fcla/etd/CFE0002535.
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Pichette, Alexandre. "Multiple model estimation and detection for adaptive guidance of hybrid systems." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=80134.
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The interception of a tactical ballistic missile (TBM) represents a great challenge to the guidance and control community as the maneuver potential of the TBM is almost in the same order as the interceptor missile. The maneuver advantage of the interceptor over the TBM being reduced, a new approach for estimation and guidance for the interception of a maneuvering TBM is presented in this research. The target is assumed to use its maneuvering potential by performing a single evasive bang-bang maneuver. A simple detection algorithm for an evasive maneuver of the target combined with the use of a multiple model estimators like the interactive multiple models (IMM) led to a new adaptive guidance law, the DGL/Adapt law. Simulations results using this approach gave a reduction in the miss distance in comparison with a static guidance law.
9
Canolla, Adriano. "Interactive Multiple Model Estimation for Unmanned Aircraft Systems Detect and Avoid." Thesis, Illinois Institute of Technology, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13419136.
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This research presents new methods to apply safety standards to Detect and Avoid (DAA) functions for Unmanned Aircraft Systems (UAS), using maneuvering target tracking and encounter models.
Previous DAA research methods focused on predefined, linear encounter generation. The new estimation and prediction methods in this research are based on the target tracking of maneuvering intruders using Multiple Model Adaptive Estimation and a realistic random encounter generation based on an established encounter model.
When tracking maneuvering intruders there is limited knowledge of changes in intruder behavior beyond the current measurement. The standard Kalman filter (KF) with a single motion model is limited in performance for such problems due to ineffective responses as the target maneuvers. In these cases, state estimation can be improved using MMAE. It is assumed that the current active dynamic model is one of a discrete set of models, each of which is the basis for a separate filter. These filters run in parallel to estimate the states of targets with changing dynamics.
In practical applications of multiple model systems, one of the most popular algorithms for the MMAE is the Interacting Multiple Model (IMM) estimator. In the IMM, the regime switching is modeled by a finite state homogeneous Markov Chain. This is represented by a transition probability matrix characterizing the mode transitions. A Markov Chain is a stochastic model describing a sequence of possible events in which the probability of each event depends only on the previous event.
This research uses the hazard states estimates (which are derived from DAA standards) to analyze the IMM performance, and then presents a new method to predict the hazard states. To reduce the prediction error, this new method accounts for maneuvering intruders. The new prediction method uses the prediction phase in the IMM algorithm to predict the future intruder aircraft states based on the current and past sensor measurements.
The estimation and prediction methods described in this thesis can help ensure safe encounters between UAS and manned aircraft in the National Airspace System through improvement of the trajectory estimation used to inform the DAA sensor certification process.
10
Khayyer, Pardis. "Multiple Model Based Estimation and Control in Large-Scale Interconnected Systems." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1385085547.
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11
Abd, El-Sallam Amar. "Low order channel estimation for CDMA systems." Curtin University of Technology, Department of Electrical and Computer Engineering, 2005. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=16299.
Full textAbstract:
New approaches and algorithms are developed for the identification and estimation of low order models that represent multipath channel effects in Code Division Multiple Access (CDMA) communication systems. Based on these parsimonious channel models, low complexity receivers such as RAKE receivers are considered to exploit these propagation effects and enhance the system performance. We consider the scenario where multipath is frequency selective slowly fading and where the channel components including delays and attenuation coefficients are assumed to be constant over one or few signalling intervals. We model the channel as a long FIR-like filter (or a tapped delay line filter) with the number of taps related to the ratio between the channel delay-spread and the chip duration. Due to the high data rate of new CDMA systems, the channel length in terms of the chip duration will be very large. With classical channel estimation techniques this will result in poor estimates of many of the channel parameters where most of them are zero leading to a reduction in the system performance. Unlike classical techniques which estimate directly the channel response given the number of taps or given an estimate of the channel length, the proposed techniques in this work will firstly identify the significant multipath parameters using model selection techniques, then estimate these identified parameters. Statistical tests are proposed to determine whether or not each individual parameter is significant. A low complexity RAKE receiver is then considered based on estimates of these identified parameters only. The level of significance with which we will make this assertion will be controlled based on statistical tests such as multiple hypothesis tests. Frequency and time domain based approaches and model selection techniques are proposed to achieve the above proposed objectives.The frequency domain approach for parsimonious channel estimation results in an efficient implementation of RAKE receivers in DS-CDMA systems. In this approach, we consider a training based strategy and estimate the channel delays and attenuation using the averaged periodogram and modified time delay estimation techniques. We then use model selection techniques such as the sphericity test and multiple hypotheses tests based on F-Statistics to identify the model order and select the significant channel paths. Simulations show that for a pre-defined level of significance, the proposed technique correctly identifies the significant channel parameters and the parsimonious RAKE receiver shows improved statistical as well as computational performance over classical methods. The time domain approach is based on the Bootstrap which is appropriate for the case when the distribution of the test statistics required by the multiple hypothesis tests is unknown. In this approach we also use short training data and model the channel response as an FIR filter with unknown length. Model parameters are then estimated using low complexity algorithms in the time domain. Based on these estimates, bootstrap based multiple hypotheses tests are applied to identify the non-zero coefficients of the FIR filter. Simulation results demonstrate the power of this technique for RAKE receivers in unknown noise environments. Finally we propose adaptive blind channel estimation algorithms for CDMA systems. Using only the spreading code of the user of interest and the received data sequence, four different adaptive blind estimation algorithms are proposed to estimate the impulse response of frequency selective and frequency non-selective fading channels. Also the idea is based on minimum variance receiver techniques. Tracking of a frequency selective varying fading channel is also considered.
A blind based hierarchical MDL model selection method is also proposed to select non-zero parameters of the channel response. Simulation results show that the proposed algorithms perform better than previously proposed algorithms. They have lower complexity and have a faster convergence rate. The proposed algorithms can also be applied to the design of adaptive blind channel estimation based RAKE receivers.
12
Fung, Chun-yu, and 馮震宇. "Estimation of fading channel in DS-CDMA multiuser communications systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B27509023.
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13
Muralidhar, Aditya. "Multiple-Input Multiple Output System on a Spinning Vehicle with Unknown Channel State Information." International Foundation for Telemetering, 2012. http://hdl.handle.net/10150/581828.
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This paper presents the investigations into the performance of a multiple-input multiple-output (MIMO) system with its transmitters on a spinning vehicle and no available channel state information (CSI) at the transmitter or the receiver. The linear least squares approach is used to estimate the channel and the estimation error is measured. Spinning gives rise to a periodic component in the channel which can be estimated based on the spin rate relative to the data rate of the system. It is also determined that spinning causes the bit error rate of the system to degrade by a few dB.
14
Xie, Yongzhe. "On adaptive transmission, signal detection and channel estimation for multiple antenna systems." Diss., Texas A&M University, 2004. http://hdl.handle.net/1969.1/1058.
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This research concerns analysis of system capacity, development of adaptive transmission schemes with known channel state information at the transmitter (CSIT) and design of new signal detection and channel estimation schemes with low complexity in some multiple antenna systems. We first analyze the sum-rate capacity of the downlink of a cellular system with multiple transmit antennas and multiple receive antennas assuming perfect CSIT. We evaluate the ergodic sum-rate capacity and show how the sum-rate capacity increases as the number of users and the number of receive antennas increases. We develop upper and lower bounds on the sum-rate capacity and study various adaptive MIMO schemes to achieve, or approach, the sum-rate capacity. Next, we study the minimum outage probability transmission schemes in a multiple-input-single-output (MISO) flat fading channel assuming partial CSIT. Considering two special cases: the mean feedback and the covariance feedback, we derive the optimum spatial transmission directions and show that the associated optimum power allocation scheme, which minimizes the outage probability, is closely related to the target rate and the accuracy of the CSIT. Since CSIT is obtained at the cost of feedback bandwidth, we also consider optimal allocation of bandwidth between the data channel and the feedback channel in order to maximize the average throughput of the data channel in MISO, flat fading, frequency division duplex (FDD) systems. We show that beamforming based on feedback CSI can achieve an average rate larger than the capacity without CSIT under a wide range of mobility conditions. We next study a SAGE-aided List-BLAST detection scheme for MIMO systems which can achieve performance close to that of the maximum-likelihood detector with low complexity. Finally, we apply the EM and SAGE algorithms in channel estimation for OFDM systems with multiple transmit antennas and compare them with a recently proposed least-squares based estimation algorithm. The EM and SAGE algorithms partition the problem of estimating a multi-input channel into independent channel estimation for each transmit-receive antenna pair, therefore avoiding the matrix inversion encountered in the joint least-squares estimation.
15
Olonbayar, Sonom [Verfasser]. "Multiple Access Techniques and Channel Estimation in OFDM Communication Systems / Sonom Olonbayar." Aachen : Shaker, 2006. http://d-nb.info/117053340X/34.
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Abdallah, Saeed. "Widely linear minimum variance channel estimation with application to multicarrier CDMA systems." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=112550.
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Conventional Minimum-Variance (MV) channel estimation is affected by two sources of error, namely the finite number of samples used to estimate the covariance matrix and the asymptotic bias due to interference and additive noise. On the other hand, widely linear (WL) filtering has been shown to improve the estimation of improper complex signals. Researchers have recently demonstrated that the application of WL processing principles can significantly improve the performance of subspace-based channel estimation algorithms. However, in contrast to MV estimation algorithms, subspace-based algorithms assume knowledge of the total number of users in the system, and must be coupled with sophisticated user enumeration algorithm at the expense of increased complexity. In this work, in an effort to combine the practical advantages of MV channel estimation algorithms with the performance of WL filters we propose a widely linear version of the MV channel estimator in the context of multicarrier(MC) CDMA systems employing real modulation. We use numerical simulations to demonstrate that the widely linear minimum-variance algorithm yields more accurate channel estimates compared to the conventional MV algorithm. By considering two simplified transmission/reception models, we also show analytically that the widely linear estimator on average reduces both types of error.
17
Wong, Kar Lun (Clarence). "Space-time-frequency channel estimation for multiple-antenna orthogonal frequency division multiplexing systems." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=100244.
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We propose a linear mean square error channel estimator that exploits the joint space-time-frequency (STF) correlations of the wireless fading channel for applications in multiple-antenna orthogonal frequency division multiplexing systems. Our work generalizes existing channel estimators to the full dimensions including transmit spatial, receive spatial, time, and frequency. This allows versatile applications of our STF channel estimator to any fading environment, ranging from spatially-uncorrelated slow-varying frequency-flat channels to spatially-correlated fast-varying frequency-selective channels.The proposed STF channel estimator reduces to a time-frequency (TF) channel estimator when no spatial correlations exist. In another perspective, the lower-dimension TF channel estimator can be viewed as an STF channel estimator with spatial correlation mismatch for space-time-frequency selective channels.
Computer simulations were performed to study the mean-square-error (MSE) behavior with different pilot parameters. We then evaluate the suitability of our STF channel estimator on a space-frequency block coded OFDM system. Bit error rate (BER) performance degradation, with respect to perfect coherent detection, is limited to less than 2 dB at a BER of 10-5 in the modified 3GPP fast-fading suburban macro environment. Modifications to the 3GPP channel involves reducing the base station angle spread to imitate a high transmit spatial correlation scenario to emphasize the benefit of exploiting spatial correlation in our STF channel estimator.
18
Kasperski, Michael William. "Multiple model estimation for linear stochastic hybrid systems with non-homogeneous transition probabilities." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101496.
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Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2015.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 61-64).
This thesis investigates the field of stochastic hybrid estimation. A broad introduction to the framework surrounding estimation, filtering, and multiple model based systems is presented. More specifically, the often made assumption of a constant time-invariant mode transition probability matrix is relaxed. Recent work done in the area of non-Markov jump stochastic hybrid systems is explored, including semi- Markov systems, non-homogeneous transition probability matrices, and continuous-state-dependent mode transitions. Algorithms needed to develop linear multiple model based filters with non-homogeneous transition probabilities are detailed. Finally, a case study for the practical implementation of an extended Kalman filter in the application of attitude heading and reference systems is conducted.
by Michael William Kasperski.
S.M.
19
Cheng, Hui. "New channel estimation and multiuser detection algorithms for multicarrier(MC)-CDMA communications systems." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B35314321.
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Björklund, Maria. "Simulation Tool for Design of Multiple Photovoltaic Systems : Estimation of System Sizes, Grid Interaction, and Area Requirements." Thesis, Högskolan Dalarna, Institutionen för information och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:du-37620.
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Photovoltaic solar power is an increasing source of energy and part of the renewable energy generation which is needed in the near future to achieve the set climate goals. When planning new photovoltaic installations, parameters which affect the design are both local conditions (e.g. weather) and system parameters such as tilt and azimuth angles. Commercial areas often have high loads during the day when solar power is available and are therefore interesting for photovoltaic installations. In order make a quick estimation of photovoltaic power potential in an area, a simulation tool which handles load profiles from multiple buildings would be desirable. The aim of this thesis project is therefore to create a tool which can simulate multiple photovoltaic systems and for each of them estimate system sizes, grid interactions, and area requirements. The simulation tool is based on Python programming with the aid of System Advisor Model, a simulation software for photovoltaic and other renewable energy tech-nologies. Optimization of orientation angles was made for clear sky with the goal of high load-generation match. Different system sizes were estimated and simulated based on different degrees of self-sufficiency, net-zero consumption, and the existing transfer capacity of the building in question. When the simulation result was compared to a detailed photovoltaic design project, some agreements between the results were found, as well as further development needs such as refining area estimation. To further develop the usability of the tool, a more user-friendly interface is needed. Other improvements could be to enable simulations of multiple direction systems and integration of the local grid structure and limitations.
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Cheng, Hui, and 成慧. "New channel estimation and multiuser detection algorithms for multicarrier(MC)-CDMA communications systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B35314321.
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Nguyen, Nam Tran Electrical Engineering & Telecommunications Faculty of Engineering UNSW. "Training signal and precoder dsigns for channel estimation and symbol detection in MIMO and OFDM systems." Awarded by:University of New South Wales. Electrical Engineering & Telecommunications, 2008. http://handle.unsw.edu.au/1959.4/43243.
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Research in wireless communications has been actively carried out in recent years. In order to enable a high data transmission rate, multiple-input multiple-output (MIMO) communications has been proposed and commonly adopted. Accurate channel identification and reliable data detection are major challenges in the implementation of a communications system operating over a wireless fading channel. These issues become even more challenging in MIMO systems since there are many more parameters involved in the estimation processes. This thesis, consisting of four major parts, focuses on applying convex optimization to solve design problems in both MIMO channel estimation and data detection. The first part proposes a novel orthogonal affine precoding technique for jointly optimal channel estimation and symbol detection in a general MIMO frequency-selective fading channel. Additionally, the optimal power allocation between the data and training signals is also analytically derived. The proposed technique is shown to perform much better than other affine precoding techniques in terms of detection error probability and computational complexity. The second part is concerned with the MIMO orthogonal frequency-division multiplexing (OFDM) systems. The superimposed training technique developed in the first part is applied and extended for MIMO-OFDM systems where all the involved transmitters and receivers are assumed to be uncorrelated. Analytical and numerical results confirm that the proposed design can efficiently identify the unknown wireless channel as well as effectively recover the data symbols, while conserving the transmission bandwidth. The third part considers training and precoding designs for OFDM under colored noise environment. The superiority of the proposed design over the previously-known design under colored noise is thoroughly demonstrated. The last part of the thesis develops the orthogonal affine precoder for spatially correlated MIMO-OFDM systems. The optimal superimposed training sequences are solved by tractable semi-definite programming. To have a better computational efficiency, two approximate design techniques are also presented. Furthermore, the non-redundancy precoder proposed in the third part is employed to combat channel correlation. As a result, the proposed designs are demonstrated to outperform other known designs in terms of channel estimation and data detection.
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Markström, Johannes. "3D Position Estimation of a Person of Interest in Multiple Video Sequences : People Detection." Thesis, Linköpings universitet, Datorseende, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-98140.
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In most cases today when a specific person's whereabouts is monitored through video surveillance it is done manually and his or her location when not seen is based on assumptions on how fast he or she can move. Since humans are good at recognizing people this can be done accurately, given good video data, but the time needed to go through all data is extensive and therefore expensive. Because of the rapid technical development computers are getting cheaper to use and therefore more interesting to use for tedious work. This thesis is a part of a larger project that aims to see to what extent it is possible to estimate a person of interest's time dependent 3D position, when seen in surveillance videos. The surveillance videos are recorded with non overlapping monocular cameras. Furthermore the project aims to see if the person of interest's movement, when position data is unavailable, could be predicted. The outcome of the project is a software capable of following a person of interest's movement with an error estimate visualized as an area indicating where the person of interest might be at a specific time. This thesis main focus is to implement and evaluate a people detector meant to be used in the project, reduce noise in position measurement, predict the position when the person of interest's location is unknown, and to evaluate the complete project. The project combines known methods in computer vision and signal processing and the outcome is a software that can be used on a normal PC running on a Windows operating system. The software implemented in the thesis use a Hough transform based people detector and a Kalman filter for one step ahead prediction. The detector is evaluated with known methods such as Miss-rate vs. False Positives per Window or Image (FPPW and FPPI respectively) and Recall vs. 1-Precision. The results indicate that it is possible to estimate a person of interest's 3D position with single monocular cameras. It is also possible to follow the movement, to some extent, were position data are unavailable. However the software needs more work in order to be robust enough to handle the diversity that may appear in different environments and to handle large scale sensor networks.
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Mody, Apurva Narendra. "Signal Acquisition and Tracking for Fixed Wireless Access Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/7624.
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The general objective of this proposed research is to design and develop signal acquisition and tracking algorithms for multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems for fixed wireless access applications. The algorithms are specifically targeted for systems that work in time division multiple access and frequency division multiple access frame modes. In our research, we first develop a comprehensive system model for a MIMO-OFDM system under the influence of the radio frequency (RF) oscillator frequency offset, sampling frequency (SF) offset, RF oscillator phase noise, frequency selective channel impairments and finally the additive white Gaussian noise. We then develop the acquisition and tracking algorithms to estimate and track all these parameters. The acquisition and tracking algorithms are assisted by a preamble consisting of one or more training sequences and pilot symbol matrices. Along with the signal acquisition and tracking algorithms, we also consider design of the MIMO-OFDM preamble and pilot signals that enable the suggested algorithms to work efficiently.
Signal acquisition as defined in our research consists of time and RF synchronization, SF offset estimation and correction, phase noise estimation and correction and finally channel estimation. Signal tracking consists of RF, SF, phase noise and channel tracking. Time synchronization, RF oscillator frequency offset, SF oscillator frequency offset, phase noise and channel estimation and tracking are all research topics by themselves. A large number of studies have addressed these issues, but usually individually and for single-input single-output (SISO) OFDM systems. In the proposed research we present a complete suite of signal acquisition and tracking algorithms for MIMO-OFDM systems along with Cramr-Rao bounds for the SISO-OFDM case. In addition, we also derive the Maximum Likelihood (ML) estimates of the parameters for the SISO-OFDM case.
Our proposed research is unique from the existing literature in that it presents a complete receiver implementation for MIMO-OFDM systems and accounts for the cumulative effects of all possible acquisition and tracking errors on the bit error rate (BER) performance. The suggested algorithms and the pilot/training schemes may be applied to any MIMO OFDM system and are independent of the space-time coding techniques that are employed.
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Sen, Mumtaz Bilgin. "Channel estimation techniques for single and multiple transmit antenna orthogonal frequency division multiplexing (OFDM) systems." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Sep%5FSen.pdf.
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Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, September 2005.Thesis Advisor(s): Roberto Cristi, Murali Tummala. Includes bibliographical references (p. 71-72). Also available online.
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Jagannatham, Aditya K. "Bandwidth efficient channel estimation for multiple-input multiple-output (MIMO) wireless communication systems a study of semi-blind and superimposed schemes /." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3250071.
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Thesis (Ph. D.)--University of California, San Diego, 2007.Title from first page of PDF file (viewed April 4, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 177-183).
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Mota, Susana de Jesus. "Channel modelling for MIMO systems." Doctoral thesis, Universidade de Aveiro, 2014. http://hdl.handle.net/10773/14961.
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Doutoramento em Engenharia ElectrotécnicaSystems equipped with multiple antennas at the transmitter and at the receiver, known as MIMO (Multiple Input Multiple Output) systems, offer higher capacities, allowing an efficient exploitation of the available spectrum and/or the employment of more demanding applications. It is well known that the radio channel is characterized by multipath propagation, a phenomenon deemed problematic and whose mitigation has been achieved through techniques such as diversity, beamforming or adaptive antennas. By exploring conveniently the spatial domain MIMO systems turn the characteristics of the multipath channel into an advantage and allow creating multiple parallel and independent virtual channels. However, the achievable benefits are constrained by the propagation channel’s characteristics, which may not always be ideal. This work focuses on the characterization of the MIMO radio channel. It begins with the presentation of the fundamental results from information theory that triggered the interest on these systems, including the discussion of some of their potential benefits and a review of the existing channel models for MIMO systems. The characterization of the MIMO channel developed in this work is based on experimental measurements of the double-directional channel. The measurement system is based on a vector network analyzer and a two-dimensional positioning platform, both controlled by a computer, allowing the measurement of the channel’s frequency response at the locations of a synthetic array. Data is then processed using the SAGE (Space-Alternating Expectation-Maximization) algorithm to obtain the parameters (delay, direction of arrival and complex amplitude) of the channel’s most relevant multipath components. Afterwards, using a clustering algorithm these data are grouped into clusters. Finally, statistical information is extracted allowing the characterization of the channel’s multipath components. The information about the multipath characteristics of the channel, induced by existing scatterers in the propagation scenario, enables the characterization of MIMO channel and thus to evaluate its performance. The method was finally validated using MIMO measurements.
Os sistemas equipados com múltiplas antenas no emissor e no recetor, conhecidos como sistemas MIMO (Multiple Input Multiple Output), oferecem capacidades mais elevadas, permitindo melhor rentabilização do espectro e/ou utilização de aplicações mais exigentes. É sobejamente sabido que o canal rádio é caracterizado por propagação multipercurso, fenómeno considerado problemático e cuja mitigação tem sido conseguida através de técnicas como diversidade, formatação de feixe ou antenas adaptativas. Explorando convenientemente o domínio espacial os sistemas MIMO transformam as características multipercurso do canal numa mais-valia e permitem criar vários canais virtuais, paralelos e independentes. Contudo, os benefícios atingíveis são condicionados pelas características do canal de propagação, que poderão não ser sempre as ideais. Este trabalho centra-se na caracterização do canal rádio para sistemas MIMO. Inicia-se com a apresentação dos resultados fundamentais da teoria da informação que despoletaram todo o entusiamo em torno deste tipo de sistemas, sendo discutidas algumas das suas potencialidades e uma revisão dos modelos existentes para sistemas MIMO. A caracterização do canal MIMO desenvolvida neste trabalho assenta em medidas experimentais do canal direcional adquiridas em dupla via. O sistema de medida é baseado num analisador de redes vetorial e numa plataforma de posicionamento bidimensional, ambos controlados por um computador, permitindo obter a resposta em frequência do canal rádio nos vários pontos correspondentes à localização dos elementos de um agregado virtual. As medidas são posteriormente processadas com o algoritmo SAGE (Space-Alternating Expectation-Maximization), de forma a obter os parâmetros (atraso, direção de chegada e amplitude complexa) das componentes multipercurso mais significativas. Seguidamente, estes dados são tratados com um algoritmo de classificação (clustering) e organizados em grupos. Finalmente é extraída informação estatística que permite caracterizar o comportamento das componentes multipercurso do canal. A informação acerca das características multipercurso do canal, induzidas pelos espalhadores (scatterers) existentes no cenário de propagação, possibilita a caracterização do canal MIMO e assim avaliar o seu desempenho. O método foi por fim validado com medidas MIMO.
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Kudathanthirige, Dhanushka Priyankara. "DESIGN AND ANALYSIS OF TRANSMISSION STRATEGIES FOR TRAINING-BASED MASSIVE MIMO SYSTEMS." OpenSIUC, 2020. https://opensiuc.lib.siu.edu/dissertations/1864.
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The next-generation wireless technologies are currently being researched to address the ever-increasing demands for higher data rates, massive connectivity, improved reliability, and extended coverage. Recently, massive multiple-input multiple-output (MIMO) has gained significant attention as a new physical-layer transmission technology that can achieve unprecedented spectral and energy efficiency gains via aggressive spatial multiplexing. Thus, massive MIMO has been one of the key enabling technologies for the fifth-generation and subsequent wireless standards. This dissertation thus focuses on developing a system, channel, and signal models by considering the practical wireless transmission impairments for massive MIMO systems, and ascertaining the viability of massive MIMO in fulfilling massive access, improved spectrum, enhanced security, and energy efficiency requirements. Specifically, new system and channel models, pilot sequence designs and channel estimation techniques, secure transmit/receive beamforming techniques, transmit power allocation schemes with enhanced security provisions, energy efficiency, and user fairness, and comprehensive performance analysis frameworks are developed for massive MIMO-aided non-orthogonal multiple access (NOMA), cognitive spectrum-sharing, and wireless relaying architectures.Our first work focuses on developing physical-layer transmission schemes for NOMA-aided massive MIMO systems. A spatial signature-based user-clustering and pilot allocation scheme is first formulated, and thereby, a hybrid orthogonal multiple access (OMA)/NOMA transmission scheme is proposed to boost the number of simultaneous connections. In our second work, the viability of invoking downlink pilots to boost the achievable rate of NOMA-aided massive MIMO is investigated. The third research contribution investigates the performance of underlay spectrum-sharing massive MIMO systems for reverse time division duplexing based transmission strategies, in which primary and secondary systems concurrently operate in opposite directions. Thereby, we show that the secondary system can be operated with its maximum average transmit power independent of the primary system in the limit of infinity many primary/secondary base-station antennas. In our fourth work, signal processing techniques, power allocation, and relay selection schemes are designed and analyzed for massive MIMO relay networks to optimize the trade-off among the achievable user rates, coverage, and wireless resource usage. Finally, the cooperative jamming and artificial noise-based secure transmission strategies are developed for massive MIMO relay networks with imperfect legitimate user channel information and with no channel knowledge of the eavesdropper. The key design criterion of the aforementioned transmission strategies is to efficiently combine the spatial multiplexing gains and favorable propagation conditions of massive MIMO with properties of NOMA, underlay spectrum-sharing, and wireless relay networks via efficient signal processing.
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Johansson, Victor. "3D Position Estimation of a Person of Interest in Multiple Video Sequences : Person of Interest Recognition." Thesis, Linköpings universitet, Datorseende, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-97970.
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Because of the increase in the number of security cameras, there is more video footage available than a human could efficiently process. In combination with the fact that computers are getting more efficient, it is getting more and more interesting to solve the problem of detecting and recognizing people automatically. Therefore a method is proposed for estimating a 3D-path of a person of interest in multiple, non overlapping, monocular cameras. This project is a collaboration between two master theses. This thesis will focus on recognizing a person of interest from several possible candidates, as well as estimating the 3D-position of a person and providing a graphical user interface for the system. The recognition of the person of interest includes keeping track of said person frame by frame, and identifying said person in video sequences where the person of interest has not been seen before. The final product is able to both detect and recognize people in video, as well as estimating their 3D-position relative to the camera. The product is modular and any part can be improved or changed completely, without changing the rest of the product. This results in a highly versatile product which can be tailored for any given situation.
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Law, Tung-man. "An iterative receiver with pilot-aided Kalman filter based channel estimation for wireless MC-CDMA communication systems." Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/hkuto/record/B38581668.
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Law, Tung-man, and 羅東文. "An iterative receiver with pilot-aided Kalman filter based channel estimation for wireless MC-CDMA communication systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B38581668.
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Atapattu, Lakmali Nadisha Kumari. "Channel tracking in SDMA-based multi-user MIMO-OFDM communications systems." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/65272/1/Lakmali_Atapattu_Thesis.pdf.
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Capacity of current and future high data rate wireless communications depend significantly on how well changes in the wireless channel are predicted and tracked. Generally, this can be estimated by transmitting known symbols. However, this increases overheads if the channel varies over time. Given today’s bandwidth demand and the increased necessity for mobile wireless devices, the contributions of this research are very significant. This study has developed a novel and efficient channel tracking algorithm that can recursively update the channel estimation for wireless broadband communications reducing overheads, therefore increasing the speed of wireless communication systems.
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Batur, Demet. "Variance Estimation in Steady-State Simulation, Selecting the Best System, and Determining a Set of Feasible Systems via Simulation." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/10541.
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In this thesis, we first present a variance estimation technique based on the standardized time series methodology for steady-state simulations. The proposed variance estimator has competitive bias and variance compared to the existing estimators in the literature. We also present the technique of rebatching to further reduce the bias and variance of our variance estimator. Second, we present two fully sequential indifference-zone procedures to select the best system from a number of competing simulated systems when best is defined by the maximum or minimum expected performance. These two procedures have parabola shaped continuation regions rather than the triangular continuation regions employed in several papers. The rocedures we present accommodate unequal and unknown ariances across systems and the use of common random numbers. However, we assume that basic observations are independent and identically normally distributed. Finally, we present procedures for finding a set of feasible or near-feasible systems among a finite number of simulated systems in the presence of multiple stochastic constraints, especially when the number of systems or constraints is large.
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Ramesh, Chithrupa, Henrik Sandberg, and Karl Henrik Johansson. "Stability analysis of multiple state-based schedulers with CSMA." KTH, Reglerteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-111461.
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In this paper, we identify sufficient conditions for Lyapunov Mean Square Stability (LMSS) of a contention-based network of first-order systems, with state-based schedulers. The stability analysis helps us to choose policies for adapting the scheduler threshold to the delay from the network and scheduler. We show that three scheduling laws can result in LMSS: constant-probability laws and additively increasing or decreasing probability laws. Our results counter the notions that increasing probability scheduling laws alone can guarantee stability of the closed-loop system, or that decreasing probability scheduling laws are required to mitigate congestion in the network.QC 20130116
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Lindström, Agnes, and Frida Persson. "Estimation of Hourly Origin Destination Trip Matrices for a Model of Norrköping." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-150135.
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During the last century, the number of car users has increased as an effect of the increasing population growth. To manage the environmental and infrastructural challenges that comes with a more congested traffic network, traffic planning has become of higher importance to analyze the current traffic state and to predict future capacity challenges and effects of investments. These analysis and evaluations are commonly performed in different traffic analysis tools, where updated and realistic traffic demand needs to be provided to ensure reasonable results. In this thesis, a macroscopic model of Norrköping municipality constructed in the traffic demand modelling software Visum and a daily Origin-Destination(OD)-matrix is considered. The goal of this thesis is to produce a method that modify the current daily demand matrix into hourly demand matrices, called hourly target matrices, that represents a typical weekday. The goal is also to implement and evaluate the OD-estimation algorithm Simultaneous Perturbation Stochastic Approximation (SPSA) to obtain updated and valid demand matrices for the network model of Norrköping. The method of dividing the daily demand matrix into hourly target matrices is based on the paper by Spiess %26 Suter (1990). The method makes use of the available daily trip purpose matrices combined with hourly link flow observations from 96 links in a multiple linear regression model to obtain 24 hourly demand matrices. The resulting matrices are compared with the link flow observations and has different levels of R^2-fit, the maximum fit is 85.79 % and the minimum fit is 55.89 %. The average R^2-value is 72 %. The OD-estimation based on SPSA is performed on the AM and PM peak hours. The algorithm is implemented in Python scripts that are called from Visum where the traffic assignments is calculated. The result is an increase in R^2-value since the link flow difference between estimated and observed link flow is decreased. In total, the estimated link flows are improved by 7.4 % in the AM peak hour and 15.6 % in the PM peak hour. The total absolute change in OD-demand is 3 871 trips for AM peak hour and 6 452 trips for the PM peak hour. The estimated OD-matrices are evaluated by qualitatively visualizing the difference in heat maps and in the quantitative measure structural similarity index. The result is no major structural change from the hourly target matrices which verifies that the information used when the target matrices is produced still is considered. The total demand increased in both hours, with 505 respectively 2 431 trips and flows in some OD-pairs has a very high percental change. This was restricted by adding a penalty term to the SPSA-algorithm on the PM peak hour. The result of penalized SPSA is a much less increase of total demand as well as less percental change of the OD-flows. Though, this to a cost of not decreasing the link flow difference in the same magnitude.
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Rübsamen, Michael [Verfasser], Alex [Akademischer Betreuer] Gershman, Nikos [Akademischer Betreuer] Sidiropoulos, Abdelhak [Akademischer Betreuer] Zoubir, and Andy [Akademischer Betreuer] Schürr. "Advanced direction-of-arrival estimation and beamforming techniques for multiple antenna systems / Michael Rübsamen. Betreuer: Alex Gershman ; Nikos Sidiropoulos ; Abdelhak Zoubir ; Andy Schürr." Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2011. http://d-nb.info/1105562646/34.
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Sattigeri, Ramachandra Jayant. "Adaptive Estimation and Control with Application to Vision-based Autonomous Formation Flight." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/16272.
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The role of vision as an additional sensing mechanism has received a lot of attention in recent years in the context of autonomous flight applications. Modern Unmanned Aerial Vehicles (UAVs) are equipped with vision sensors because of their light-weight, low-cost characteristics and also their ability to provide a rich variety of information of the environment in which the UAVs are navigating in. The problem of vision based autonomous flight is very difficult and challenging since it requires bringing together concepts from image processing and computer vision, target tracking and state estimation, and flight guidance and control.
This thesis focuses on the adaptive state estimation, guidance and control problems involved in vision-based formation flight. Specifically, the thesis presents a composite adaptation approach to the partial state estimation of a class of nonlinear systems with unmodeled dynamics. In this approach, a linear time-varying Kalman filter is the nominal state estimator which is augmented by the output of an adaptive neural network (NN) that is trained with two error signals. The benefit of the proposed approach is in its faster and more accurate adaptation to the modeling errors over a conventional approach.
The thesis also presents two approaches to the design of adaptive guidance and control (G&C) laws for line-of-sight formation flight. In the first approach, the guidance and autopilot systems are designed separately and then combined together by assuming time-scale separation. The second approach is based on integrating the guidance and autopilot design process. The developed G&C laws using both approaches are adaptive to unmodeled leader aircraft acceleration and to own aircraft aerodynamic uncertainties.
The thesis also presents theoretical justification based on Lyapunov-like stability analysis for integrating the adaptive state estimation and adaptive G&C designs. All the developed designs are validated in nonlinear, 6DOF fixed-wing aircraft simulations.
Finally, the thesis presents a decentralized coordination strategy for vision-based multiple-aircraft formation control. In this approach, each aircraft in formation regulates range from up to two nearest neighboring aircraft while simultaneously tracking nominal desired trajectories common to all aircraft and avoiding static obstacles.
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Orjuela, Rodolfo. "Contribution à l'estimation d'état et au diagnostic des systèmes représentés par des multimodèles." Phd thesis, Institut National Polytechnique de Lorraine - INPL, 2008. http://tel.archives-ouvertes.fr/tel-00359631.
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Nombreux sont les problèmes classiquement rencontrés dans les sciences de l'ingénieur dont la résolution fait appel à l'estimation d'état d'un système par le biais d'un observateur. La synthèse d'un observateur n'est envisageable qu'à la condition de disposer d'un modèle à la fois exploitable et représentatif du comportement dynamique du système. Or, la modélisation du système et la synthèse de l'observateur deviennent des tâches difficiles à accomplir dès lors que le comportement dynamique du système doit être représenté par un modèle de nature non linéaire. Face à ces difficultés, l'approche multimodèle peut être mise à profit.Les travaux présentés dans cette thèse portent sur les problèmes soulevés par l'identification, l'estimation d'état et le diagnostic de systèmes non linéaires représentés à l'aide d'un multimodèle découplé. Ce dernier, composé de sous-modèles qui peuvent être de dimensions différentes, est doté d'un haut degré de généralité et de flexibilité et s'adapte particulièrement bien à la modélisation des systèmes complexes à structure variable. Cette caractéristique le démarque des approches multimodèles plus conventionnelles qui ont recours à des sous-modèles de même dimension.
Après une brève introduction à l'approche multimodèle, le problème de l'estimation paramétrique du multimodèle découplé est abordé. Puis sont présentés des algorithmes de synthèse d'observateurs d'état robustes vis-à-vis des perturbations, des incertitudes paramétriques et des entrées inconnues affectant le système. Ces algorithmes sont élaborés à partir de trois types d'observateurs dits à gain proportionnel, à gain proportionnel-intégral et à gain multi-intégral. Enfin, les différentes phases d'identification, de synthèse d'observateurs et de génération d'indicateurs de défauts sont illustrées au moyen d'un exemple académique de diagnostic du fonctionnement d'un bioréacteur.
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Wang, Xudong. "Vehicle health monitoring system using multiple-model adaptive estimation." Thesis, University of Hawaii at Manoa, 2003. http://hdl.handle.net/10125/7051.
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In this thesis, we propose two failure detection and identification (FDI) approaches based on the multiple-model estimation algorithm to monitor the health of vehicles, specifically aircraft applications. They detect and identify failing components of the vehicle, and the system variations. The dynamics of the vehicle are modeled as a stochastic hybrid system with uncertainty-unknown model structure or parameters. FDI performance is evaluated for each approach. We demonstrate the reliability, validity of these approaches by applying them to simulate aircraft machinery experiencing component failures or structural variations. The approaches that we surveyed are: (i) Multiple-Hypothesis Kalman Filter, and (ii) Interacting Multiple-Model (IMM) Estimator. By coupling the fault detection and identification (FDI) scheme with the reconfigurable controller design scheme, a fault-tolerant control system based on the multiple-model estimation algorithm is defined.vii, 59 leaves
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Sakamaki, Joshua Y. "Cooperative Estimation for a Vision-Based Multiple Target Tracking System." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/6072.
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In this thesis, the Recursive-Random Sample Consensus (R-RANSAC) algorithm is applied to a vision-based, cooperative target tracking system. Unlike previous applications, which focused on a single camera platform tracking targets in the image frame, this work uses multiple camera platforms to track targets in the inertial or world frame. The process of tracking targets in the inertial frame is commonly referred to as geolocation.In practical applications sensor biases cause the geolocated target estimates to be biased from truth. The method for cooperative estimation developed in this thesis first estimates the relative rotational and translational biases that exist between tracks from different vehicles. It then accounts for the biases and performs the track-to-track association, which determines if the tracks originate from the same target. The track-to-track association is based on a sliding window approach that accounts for the correlation between tracks sharing common process noise and the correlation in time between individual estimation errors, yielding a chi-squared distribution. Typically, accounting for the correlation in time requires the inversion of a Nnx x Nnx covariance matrix, where N is the length of the window and nx is the number of states. Note that this inversion must occur every time the track-to-track association is to be performed. However, it is shown that by making a steady-state assumption, the inverse has a simple closed-form solution, requiring the inversion of only two nx x nx matrices, and can be calculated offline. Distributed data fusion is performed on tracks where the hypothesis test is satisfied. The proposed method is demonstrated on data collected from an actual vision-based tracking system.A novel method is also developed to cooperatively estimate the location and size of occlusions. This capability is important for future target tracking research involving optimized path planning/gimbal pointing, where a geographical map is unavailable. The method is demonstrated in simulation.
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Vestin, Albin, and Gustav Strandberg. "Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms." Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.
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Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, instead of filtering to estimate the true target states. With this method, validation data for online, causal, target tracking algorithms can be obtained for all traffic scenarios without the need of extra sensors. We investigate how non-causal algorithms affects the target tracking performance using multiple sensors and dynamic models of different complexity. This is done to evaluate real-time methods against estimates obtained from non-causal filtering. Two different measurement units, a monocular camera and a LIDAR sensor, and two dynamic models are evaluated and compared using both causal and non-causal methods. The system is tested in two single object scenarios where ground truth is available and in three multi object scenarios without ground truth. Results from the two single object scenarios shows that tracking using only a monocular camera performs poorly since it is unable to measure the distance to objects. Here, a complementary LIDAR sensor improves the tracking performance significantly. The dynamic models are shown to have a small impact on the tracking performance, while the non-causal application gives a distinct improvement when tracking objects at large distances. Since the sequence can be reversed, the non-causal estimates are propagated from more certain states when the target is closer to the ego vehicle. For multiple object tracking, we find that correct associations between measurements and tracks are crucial for improving the tracking performance with non-causal algorithms.
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Sousa, Jeovane Vicente de. "Computação em nuvem no contexto das smart grids: uma aplicação para auxílio à localização de faltas em sistemas de distribuição." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/18/18154/tde-30102018-100504/.
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A computação em nuvem tem sido vislumbrada como a principal tecnologia capaz de integrar e gerenciar os diversos sistemas envolvidos em uma Smart Grid. Nesse sentido, esta pesquisa tem por objetivo desenvolver uma infraestrutura de computação em nuvem capaz de armazenar e manipular dados em sistemas de distribuição. Analisando a infraestrutura das principais aplicações que utilizam computação em nuvem nesse contexto, foi proposta uma arquitetura com serviços essenciais, que pode ser estendida, para abrigar serviços e aplicações voltadas aos sistemas de distribuição inteligentes. A partir dessa proposta, uma infraestrutura de computação em nuvem foi implementada, utilizando ferramentas open source. Essa infraestrutura permitiu o desenvolvimento de uma nova aplicação para auxílio à localização de faltas, utilizando mineração de dados sobre os dados provenientes de smart meters, que é capaz de reduzir o problema da múltipla estimação nos sistemas de distribuição radial, auxiliando na definição do ramal faltoso. Para isso, uma versão otimizada da ferramenta de mineração de dados DAMICORE (Data Mining of Code Repositories) foi implementada estendendo os serviços básicos da arquitetura proposta. A aplicação desenvolvida foi avaliada utilizando centenas de simulações de falta sujeitas ao problema da múltipla estimação, aplicadas ao longo de um alimentador de testes, sendo capaz de reduzir mais de 80% das extensões de falta susceptíveis ao problema da múltipla estimação. Os resultados apresentados mostraram que a arquitetura proposta e a infraestrutura de computação em nuvem desenvolvida são capazes de suportar novas aplicações para os sistemas de distribuição inteligentes contribuindo para o desenvolvimento das smart grids e para a difusão da computação em nuvem nesse contexto. Como contribuição adicional, a aplicação em nuvem desenvolvida permitirá reduzir a múltipla estimação na localização de faltas em sistemas de distribuição.Cloud computing has been envisioned as the main technology capable to integrate and manage many systems on a Smart Grid. Thus, this research aims to develop a cloud computing infrastructure to store and manipulate smart distribution system data. By analyzing the infrastructure of the main applications using cloud computing for smart distribution systems, an extensible architecture with essential services was proposed to host smart distribution systems services and applications. Based on this proposition, a cloud computing platform was developed using open source tools. A new application to reduce multiple estimation for fault location in radial distribution systems using datamining techniques over smart meter data was implemented using this infrastructure. An optimized version of the datamining tool known as DAMICORE (Data Mining of Code Repositories) was implemented as an extension to the proposed architecture basic services. The new cloud application was tested using hundreds of fault simulations through a test feeder, being able to reduce the line extensions with multiple estimation by more than 80% in the simulated fault cases. The results show that the proposed cloud computing architecture and infrastructure enable new smart distribution systems applications, contributing to the development of smart grids and diffusion of cloud computing in this context. As an additional contribution, the cloud application developed will help to reduce the multiple estimation for fault locations in distribution systems.
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Sauerwein, Andrea C. "Estimations of dipolar couplings in multiple-spin systems by solid state NMR." Thesis, University of Southampton, 2010. https://eprints.soton.ac.uk/191325/.
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Costa, Michele Nazareth da. "Codage spatio-temporel tensoriel pour les systèmes de communication sans fil MIMO." Thesis, Nice, 2014. http://www.theses.fr/2014NICE4014/document.
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Depuis le succès croissant des systèmes mobiles au cours des années 1990, les nouvelles technologies sans fil ont été développées afin de répondre à la demande croissante de services multimédias de haute qualité avec des taux d'erreur les plus faibles possibles. Un moyen intéressant pour améliorer les performances et obtenir de meilleurs taux de transmission consiste à combiner l'utilisation de plusieurs diversités avec un accès de multiplexage dans le cadre des systèmes MIMO. L'utilisation de techniques de sur-échantillonnage, d'étalement et de multiplexage, et de diversités supplémentaires conduit à des signaux multidimensionnels, au niveau de la réception, qui satisfont des modèles tensoriels. Cette thèse propose une nouvelle approche tensorielle basée sur un codage spatio-temporel tensoriel (TST) pour les systèmes de communication sans fil MIMO. Les signaux reçus par plusieurs antennes forment un tenseur d'ordre quatre qui satisfait un nouveau modèle tensoriel, modèle PARATUCK-(2,4) (PT-(2,4)). Une analyse de performance est réalisée pour le système TST ainsi que pour un système spatio-temporel-fréquentiel (STF) récemment proposé dans la littérature, avec l'obtention du gain maximum de diversité dans le cas d'un canal à évanouissement plat. Un système de transmission basé sur le codage TST est proposé pour les systèmes MIMO avec plusieurs utilisateurs. Une nouvelle décomposition tensorielle est introduite, appelée PT-(N1,N). Cette thèse établit les conditions d'unicité du modèle PT-(N1,N). À partir de ces résultats, différents récepteurs semi-aveugles sont proposés pour une estimation conjointe des symboles transmis et du canal, pour les systèmes TST et STFSince the growing success of mobile systems in the 1990s, new wireless technologies have been developed in order to support a growing demand for high-quality multimedia services with low error rates. An interesting way to improve the error performance and to achieve better transmission rates is to combine the use of various diversities and multiplexing access techniques in the MIMO system context. The incorporation of oversampling, spreading and multiplexing operations and additional diversities on wireless systems lead to multidimensional received signals which naturally satisfy tensor models. This thesis proposes a new tensorial approach based on a tensor space-time (TST) coding for MIMO wireless communication systems. The signals received by multiple antennas form a fourth-order tensor that satisfies a new tensor model, referred to as PARATUCK-(2,4) (PT-(2,4)) model. A performance analysis is carried out for the proposed TST system and a recent space-time-frequency (STF) system, which allows to derive expressions for the maximum diversity gain over a at fading channel. An uplink processing based on the TST coding with allocation resources is proposed. A new tensor decomposition is introduced, the so-called PT-(N1,N), which generalizes the standard PT-2 and our PT-(2,4) model. This thesis establishes uniqueness conditions for the PARATUCK-(N1,N) model. From these results, joint symbol and channel estimation is ensured for the TST and STF systems. Semi-blind receivers are proposed based on the well-known Alternating Least Squares algorithm and the Levenberg-Marquardt method, and also a new receiver based on the Kronecker Least Squares (KLS) for both systems
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Rolim, Fernandes Carlos Alexandre. "Nonlinear MIMO communication systems : channel estimation and information recovery using Volterra models." Nice, 2009. http://www.theses.fr/2009NICE4002.
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Cette thèse introduit de nouvelles méthodes de traitement du signal avec des applications pour les systèmes de communications radio-mobiles. Basés sur les relations de symétrie et de redondance des cumulants d’ordre 4 des signaux de sortie du canal, nous traitons le problème de l’identification aveugle de canaux en utilisant la décomposition Parafac du tenseur des cumulants. Nous développons des algorithmes d’identification aveugles basés sur une minimisation de type moindres carrés à pas unique (SS-LS), permettant d’éviter toute sorte de traitement au préalable. L’approche SS-LS induit une solution bas » sur une seule procédure d’optimisation. En exploitant le concept de réseau virtuel, nous abordons aussi le problème de la localisation de sources dans le cadre d’un réseau d’antennes multiutilisateur, dans le but d’augmenter le nombre de capteurs virtuels pour améliorer la résolution réseau sans faire appel aux statistiques d’ordre 6. Nous traitons par ailleurs le problème de l’estimation des paramètres physiques d’un canal de communication de type MIMO à trajets multiples. En utilisant un formalisme tensoriel, nous proposons une nouvelle technique d’estimation non-paramétrique des coefficient d’un modèle MIMO convolutif, généralisant les méthodes proposées dans les chapitres précédents. Les paramètres du canal sont obtenus à l’aide d’un technique combinée de type ALS-MUSIC, basée sur un algorithme de sous-espaces. Enfin, nous considérons le problème de la détermination d’ordre du canal dans le contexte des systèmes MISO. L’algorithme proposé, basé sur une technique de déflation, détecte les sources, détermine l’ordre des canaux et estime les coefficients associésThis thesis introduces new statistical signal processing tools with applications in radio-mobile communication systems. Exploiting the symmetry and redundancy relationships of the 4th-order out-put cumulants, we address the blind channel identification problem by using the Parallel Factor (Parafac) decomposition of the cumulant tensor. We develop blind identification algorithms based on a single-step least squares (SS-LS) minimization problem, enabling us to avoid any kind of pre-processing. The SS-LS approach induces a solution based on a sole optimization procedure. Making use of the Virtual Array concept, we also treat the source localization problem in a multiuser sensor array context in order to provide additional virtual sensors, thus improving the array resolution without resorting to 6th-order statistics. In addition, we consider the problem of estimating the physical parameters of a multipath MIMO communication channel. Using a tensor formalism, we propose a new non-parametric technique to estimate the coefficients of a convolutive MIMO model, so generalizing the methods proposed in the former chapters. We obtain the physical channel parameters by means of a combined ALS-MUSIC technique base on a subspace algorithm. Finally, we turn our attention to the problem of determining the order of FIR channels in the context of MISO systems. The proposed algorithm successively detects the signal sources, determines the order of their individual transmission channels and estimates the associated channel coefficients using a deflationary approach
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Lagunas, Morales José Luis. "Joint signal detection and channel estimation in rank-deficient MIMO systems." Doctoral thesis, Université Laval, 2012. http://hdl.handle.net/20.500.11794/23565.
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L'évolution de la prospère famille des standards 802.11 a encouragé le développement des technologies appliquées aux réseaux locaux sans fil (WLANs). Pour faire face à la toujours croissante nécessité de rendre possible les communications à très haut débit, les systèmes à antennes multiples (MIMO) sont une solution viable. Ils ont l'avantage d'accroître le débit de transmission sans avoir recours à plus de puissance ou de largeur de bande. Cependant, l'industrie hésite encore à augmenter le nombre d'antennes des portables et des accésoires sans fil. De plus, à l'intérieur des bâtiments, la déficience de rang de la matrice de canal peut se produire dû à la nature de la dispersion des parcours de propagation, ce phénomène est aussi occasionné à l'extérieur par de longues distances de transmission. Ce projet est motivé par les raisons décrites antérieurement, il se veut un étude sur la viabilité des transcepteurs sans fil à large bande capables de régulariser la déficience de rang du canal sans fil. On vise le développement des techniques capables de séparer M signaux co-canal, même avec une seule antenne et à faire une estimation précise du canal. Les solutions décrites dans ce document cherchent à surmonter les difficultés posées par le medium aux transcepteurs sans fil à large bande. Le résultat de cette étude est un algorithme transcepteur approprié aux systèmes MIMO à rang déficient.
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Adduri, Phani R. "ROBUST ESTIMATION OF RELIABILITY IN THE PRESENCE OF MULTIPLE FAILURE MODES." Wright State University / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=wright1166045748.
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Barrows, Andrew Kevin. "Development and inflight validation of an automated flight planning system using multiple-sensor windfield estimation." Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/46422.
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Smith, Tiziana. "Estimating hydrologic fluxes, crop water use, and agricultural land use in China from multiple data sources." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104166.
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Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2016.Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, Institute for Data, Systems, and Society, Technology and Policy Program, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 95-99).
Crop production has significantly altered the terrestrial environment by changing land use (Ramankutty et al., 2008) and by altering the water cycle through both co-opting rainfall and surface water withdrawals (Postel et al., 1996). As the world's population continues to grow and individual diets become more resource-intensive, the demand for food - and the land and water necessary to produce it - will continue to increase. Quantitative data about water availability, water use, and agricultural land use are needed to develop sustainable water and agricultural planning and policies. However, existing large-scale data are susceptible to errors and can be physically inconsistent. China is an example of a large area where food demand is expected to increase and a lack of data clouds the resource management dialogue. Some assert that China will have insufficient land and water resources to feed itself, posing a threat to global food security if they seek to increase food imports (Brown and Starke, 1995). Others believe resources are plentiful (Lomborg, 2001). Without quantitative data, it is difficult to discern if these concerns are realistic or overly dramatized. This thesis presents a quantitative approach to characterize hydrologic fluxes, crop water use, and agricultural land use and applies the methodology in China using data from around the year 2000. The approach uses the principles of water balance and of crop water requirements to assimilate existing data with a least-squares estimation technique, producing new estimates of water and land use variables that are physically consistent while minimizing differences from measured data. We argue that this technique for estimating water fluxes and agricultural land use can provide a useful basis for resource management and policy, both in China and around the world.
by Tiziana Smith.
S.M.
S.M. in Technology and Policy
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Healey, Christopher M. "Advances in ranking and selection: variance estimation and constraints." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34768.
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In this thesis, we first show that the performance of ranking and selection (R&S) procedures in steady-state simulations depends highly on the quality of the variance estimates that are used. We study the performance of R&S procedures using three variance estimators --- overlapping area, overlapping Cramer--von Mises, and overlapping modified jackknifed Durbin--Watson estimators --- that show better long-run performance than other estimators previously used in conjunction with R&S procedures for steady-state simulations. We devote additional study to the development of the new overlapping modified jackknifed Durbin--Watson estimator and demonstrate some of its useful properties.
Next, we consider the problem of finding the best simulated system under a primary performance measure, while also satisfying stochastic constraints on secondary performance measures, known as constrained ranking and selection. We first present a new framework that allows certain systems to become dormant, halting sampling for those systems as the procedure continues. We also develop general procedures for constrained R&S that guarantee a nominal probability of correct selection, under any number of constraints and correlation across systems. In addition, we address new topics critical to efficiency of the these procedures, namely the allocation of error between feasibility check and selection, the use of common random numbers, and the cost of switching between simulated
systems.