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  • 251.
    Andersson, Joel
    et al.
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematics (Div.).
    Strömberg, Jan-Olov
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematics (Div.).
    On the Theorem of Uniform Recovery of Random Sampling Matrices2014In: IEEE Transactions on Information Theory, ISSN 0018-9448, E-ISSN 1557-9654, Vol. 60, no 3, p. 1700-1710Article in journal (Refereed)
    Abstract [en]

    We consider two theorems from the theory of compressive sensing. Mainly a theorem concerning uniform recovery of random sampling matrices, where the number of samples needed in order to recover an s-sparse signal from linear measurements (with high probability) is known to be m greater than or similar to s(ln s)(3) ln N. We present new and improved constants together with what we consider to be a more explicit proof. A proof that also allows for a slightly larger class of m x N-matrices, by considering what is called effective sparsity. We also present a condition on the so-called restricted isometry constants, delta s, ensuring sparse recovery via l(1)-minimization. We show that delta(2s) < 4/root 41 is sufficient and that this can be improved further to almost allow for a sufficient condition of the type delta(2s) < 2/3.

  • 252.
    Andersson, Julius
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics and Logistics.
    Engström, David
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics and Logistics.
    A study in how to inject steganographic data into videos in a sturdy and non-intrusive manner2019Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    It is desirable for companies to be able to hide data inside videos to be able to find the source of any unauthorised sharing of a video. The hidden data (the payload) should damage the original data (the cover) by an as small amount as possible while also making it hard to remove the payload without also severely damaging the cover. It was determined that the most appropriate place to hide data in a video was in the visual information, so the cover is an image. Two injection methods were developed and three methods for attacking the payload. One injection method changes the pixel values of an image directly to hide the payload and the other transforms the image to cosine waves that represented the image and it then changes those cosine waves to hide the payload. Attacks were developed to test how hard it was to remove the hidden data. The methods for attacking the payload where to add and remove a random value to each pixel, to set all bits of a certain importance to 1 or to compress the image with JPEG. The result of the study was that the method that changed the image directly was significantly faster than the method that transformed the image and it had a capacity for a larger payload. The injection methods protected the payload differently well against the various attacks so which method that was the best in that regard depends on the type of attack.

  • 253.
    Andersson, Kenneth
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Westin, Carl-Fredrik
    Laboratory of Mathematics in Imaging, Harvard Medical School, Brigham and Women's Hospital, Boston, USA.
    Knutsson, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, The Institute of Technology.
    Prediction from off-grid samples using continuous normalized convolution2007In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 87, no 3, p. 353-365Article in journal (Refereed)
    Abstract [en]

    This paper presents a novel method for performing fast estimation of data samples on a desired output grid from samples on an irregularly sampled grid. The output signal is estimated using integration of signals over a neighbourhood employing a local model of the signal using discrete filters. The strength of the method is demonstrated in motion compensation examples by comparing to traditional techniques.

  • 254.
    Andersson, Mats
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Burdakov, Oleg
    Linköping University, Department of Mathematics, Optimization . Linköping University, The Institute of Technology.
    Knutsson, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Zikrin, Spartak
    Linköping University, Department of Mathematics. Linköping University, The Institute of Technology.
    Sparsity Optimization in Design of Multidimensional Filter Networks2013Report (Other academic)
    Abstract [en]

    Filter networks is a powerful tool used for reducing the image processing time, while maintaining its reasonably high quality.They are composed of sparse sub-filters whose low sparsity ensures fast image processing.The filter network design is related to solvinga sparse optimization problem where a cardinality constraint bounds above the sparsity level.In the case of sequentially connected sub-filters, which is the simplest network structure of those considered in this paper, a cardinality-constrained multilinear least-squares (MLLS) problem is to be solved. If to disregard the cardinality constraint, the MLLS is typically a large-scale problem characterized by a large number of local minimizers. Each of the local minimizers is singular and non-isolated.The cardinality constraint makes the problem even more difficult to solve.An approach for approximately solving the cardinality-constrained MLLS problem is presented.It is then applied to solving a bi-criteria optimization problem in which both thetime and quality of image processing are optimized. The developed approach is extended to designing filter networks of a more general structure. Its efficiency is demonstrated by designing certain 2D and 3D filter networks. It is also compared with the existing approaches.

  • 255.
    Andersson Naesseth, Christian
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Machine learning using approximate inference: Variational and sequential Monte Carlo methods2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Automatic decision making and pattern recognition under uncertainty are difficult tasks that are ubiquitous in our everyday life. The systems we design, and technology we develop, requires us to coherently represent and work with uncertainty in data. Probabilistic models and probabilistic inference gives us a powerful framework for solving this problem. Using this framework, while enticing, results in difficult-to-compute integrals and probabilities when conditioning on the observed data. This means we have a need for approximate inference, methods that solves the problem approximately using a systematic approach. In this thesis we develop new methods for efficient approximate inference in probabilistic models.

    There are generally two approaches to approximate inference, variational methods and Monte Carlo methods. In Monte Carlo methods we use a large number of random samples to approximate the integral of interest. With variational methods, on the other hand, we turn the integration problem into that of an optimization problem. We develop algorithms of both types and bridge the gap between them.

    First, we present a self-contained tutorial to the popular sequential Monte Carlo (SMC) class of methods. Next, we propose new algorithms and applications based on SMC for approximate inference in probabilistic graphical models. We derive nested sequential Monte Carlo, a new algorithm particularly well suited for inference in a large class of high-dimensional probabilistic models. Then, inspired by similar ideas we derive interacting particle Markov chain Monte Carlo to make use of parallelization to speed up approximate inference for universal probabilistic programming languages. After that, we show how we can make use of the rejection sampling process when generating gamma distributed random variables to speed up variational inference. Finally, we bridge the gap between SMC and variational methods by developing variational sequential Monte Carlo, a new flexible family of variational approximations.

  • 256.
    Andersson Naesseth, Christian
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Vision and Radar Sensor Fusion for Advanced Driver Assistance Systems2013Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The World Health Organization predicts that by the year 2030, road traffic injuries will be one of the top five leading causes of death. Many of these deaths and injuries can be prevented by driving cars properly equipped with state-of-the-art safety and driver assistance systems. Some examples are auto-brake and auto-collision avoidance which are becoming more and more popular on the market today. A recent study by a Swedish insurance company has shown that on roadswith speeds up to 50 km/h an auto-brake system can reduce personal injuries by up to 64 percent. In fact in an estimated 40 percent of crashes, the auto-brake reduced the effects to the degree that no personal injury was sustained.

    It is imperative that these so called Advanced Driver Assistance Systems, to be really effective, have good situational awareness. It is important that they have adequate information of the vehicle’s immediate surroundings. Where are other cars, pedestrians or motorcycles relative to our own vehicle? How fast are they driving and in which lane? How is our own vehicle driving? Are there objects in the way of our own vehicle’s intended path? These and many more questions can be answered by a properly designed system for situational awareness.

    In this thesis we design and evaluate, both quantitatively and qualitatively, sensor fusion algorithms for multi-target tracking. We use a combination of camera and radar information to perform fusion and find relevant objects in a cluttered environment. The combination of these two sensors is very interesting because of their complementary attributes. The radar system has high range resolution but poor bearing resolution. The camera system on the other hand has a very high bearing resolution. This is very promising, with the potential to substantially increase the accuracy of the tracking system compared to just using one of the two. We have also designed algorithms for path prediction and a first threat awareness logic which are both qualitively evaluated.

  • 257.
    Andersson, Thord
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Läthén, Gunnar
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology.
    Lenz, Reiner
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Modified Gradient Search for Level Set Based Image Segmentation2013In: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 22, no 2, p. 621-630Article in journal (Refereed)
    Abstract [en]

    Level set methods are a popular way to solve the image segmentation problem. The solution contour is found by solving an optimization problem where a cost functional is minimized. Gradient descent methods are often used to solve this optimization problem since they are very easy to implement and applicable to general nonconvex functionals. They are, however, sensitive to local minima and often display slow convergence. Traditionally, cost functionals have been modified to avoid these problems. In this paper, we instead propose using two modified gradient descent methods, one using a momentum term and one based on resilient propagation. These methods are commonly used in the machine learning community. In a series of 2-D/3-D-experiments using real and synthetic data with ground truth, the modifications are shown to reduce the sensitivity for local optima and to increase the convergence rate. The parameter sensitivity is also investigated. The proposed methods are very simple modifications of the basic method, and are directly compatible with any type of level set implementation. Downloadable reference code with examples is available online.

  • 258. Andersson, Tobias
    et al.
    Sellergren, Albin
    Toft, Jonathan
    Signal processing through electroencephalography: Independent project in electrical engineering2016Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
  • 259. Andersson, Tobias
    et al.
    Thurley, Matthew
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Minimizing profile error when estimating the sieve-size distribution of iron ore pellets using ordinal logistic regression2011In: Powder Technology, ISSN 0032-5910, E-ISSN 1873-328X, Vol. 206, no 3, p. 218-226Article in journal (Refereed)
    Abstract [en]

    Size measurement of pellets in industry is usually performed by manual sampling and sieving techniques. Automatic on-line analysis of pellet size based on image analysis techniques would allow non-invasive, frequent and consistent measurement. We evaluate the statistical significance of the ability of commonly used size and shape measurement methods to discriminate among different sieve-size classes using multivariate techniques. Literature review indicates that earlier works did not perform this analysis and selected a sizing method without evaluating its statistical significance. Backward elimination and forward selection of features are used to select two feature sets that are statistically significant for discriminating among different sieve-size classes of pellets. The diameter of a circle of equivalent area is shown to be the most effective feature based on the forward selection strategy, but an unexpected five-feature classifier is the result using the backward elimination strategy. The discrepancy between the two selected feature sets can be explained by how the selection procedures calculate a feature's significance and that the property of the 3D data provides an orientational bias that favours combination of Feret-box measurements. Size estimates of the surface of a pellet pile using the two feature sets show that the estimated sieve-size distribution follows the known sieve-size distribution.

  • 260.
    Andersson, Tobias
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Thurley, Matthew
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Visibility classification of rocks in piles2008In: Digital Image Computing: Techniques and Applications: DICTA 2008 ; [Conference on Digital Image Computing: Techniques and Applications] ; 1 - 3 December 2008, Canberra, Australia ; proceedings, IEEE Communications Society, 2008, p. 207-213Conference paper (Refereed)
    Abstract [en]

    Size measurement of rocks is usually performed by manual sampling and sieving techniques. Automatic on-line analysis of rock size based on image analysis techniques would allow non-invasive, frequent and consistent measurement. In practical measurement systems based on image analysis techniques, the surface of rock piles will be sampled and therefore contain overlapping rock fragments. It is critical to identify partially visible rock fragments for accurate size measurements. In this research, statistical classification methods are used to discriminate rocks on the surface of a pile between entirely visible and partially visible rocks. The feature visibility ratio is combined with commonly used 2D shape features to evaluate whether 2D shape features can improve classification accuracies to minimize overlapped particle error.

  • 261. Andersson, Tobias
    et al.
    Thurley, Matthew
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Carlson, Johan E.
    A machine vision system for estimation of size distributions by weight of limestone particles during ship loading2012In: Minerals Engineering, ISSN 0892-6875, E-ISSN 1872-9444, Vol. 25, no 1, p. 38-46Article in journal (Refereed)
    Abstract [en]

    The size distribution as a function of weight of particles is an important measure of product quality in the mining and aggregates industries. When using manual sampling and sieving, the weight of particles is readily available. However, when using a machine vision system, the particle size distributions are determined as a function of the number of particles. In this paper we first show that there can be a significant weight-transformation error when transforming from one type of size distribution to another. We also show how the problem can be overcome by training a classifier and scaling the results according to calibrated average weights of rocks. The performance of the algorithm is demonstrated with results of measurements of limestone particles on conveyor belts.

  • 262. Andersson, Tobias
    et al.
    Thurley, Matthew
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Marklund, Olov
    Pellet size estimation using spherical fitting2007In: 2007 IEEE Instrumentation and Measurement Technology Conference Proceedings: Warsaw, Poland, 1 - 3 May 2007, Piscataway, NJ: IEEE Communications Society, 2007, p. 1-5Conference paper (Refereed)
    Abstract [en]

    Evaluation of Spherical Fitting as a technique for sizing iron ore pellets is performed. Size measurement of pellet in industry is usually performed by manual sampling and sieving techniques. Automatic on-line analysis of pellet size would allow non-invasive, frequent and consistent measurement. Previous work has used an assumption that pellets are spherical to estimate pellet sizes. In this research we use a 3D laser camera system in a laboratory environment to capture 3D surface data of pellets and steel balls. Validation of the 3D data against a spherical model has been performed and demonstrates that pellets are not spherical and have physical structures that a spherical model cannot capture.

  • 263. Andersson, Tobias
    et al.
    Thurley, Matthew
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Marklund, Olov
    Visibility classification of pellets in piles for sizing without overlapped particle error2008In: 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications: DICTA 2007 ; 3 - 5 Dec. 2007, Glenelg, [Adelaide], South Australia ; pPiscataway, NJ oceedings / [ed] Murk J. Bottema, IEEE Communications Society, 2008, p. 508-514Conference paper (Refereed)
    Abstract [en]

    Size measurement of pellets in industry is usually performed by manual sampling and sieving techniques. Automatic on-line analysis of pellet size based on image analysis techniques would allow non-invasive, frequent and consistent measurement. We make a distinction between entirely visible and partially visible pellets. This is a significant distinction as the size of partially visible pellets cannot be correctly estimated with existing size measures and would bias any size estimate. Literature review indicates that other image analysis techniques fail to make this distinction. Statistical classification methods are used to discriminate pellets on the surface of a pile between entirely visible and partially visible pellets. Size estimates of the surface of a pellet pile show that the overlapped particle error is overcome by only estimating the surface size distribution with entirely visible pellets.

  • 264.
    Andersson, Tomas
    KTH, School of Electrical Engineering (EES).
    Parameter Estimation and Waveform Fitting for Narrowband Signals2005Doctoral thesis, monograph (Other scientific)
    Abstract [en]

    Frequency estimation has been studied for a large number of years. One reason for this is that the problem is easy to understand, but difficult to solve. Another reason, for sure, is the large number of applications that involve frequency estimation, e.g radar using frequency modulated continuous wave (FMCW) techniques where the distance to the target is embedded in the frequency, resonance sensor systems where the output signal is given as the frequency displacement from a nominal frequency, radio frequency identification systems (RFID) where frequency modulation is used in the communication link, etc. The requirement on the frequency estimator varies with the application and typical issues include: accuracy, precision or (bias) processing speed or complexity, and ability to handle multiple signals. A lot of solutions to different problems in this area has been proposed, but still several open questions remain. The first part of this thesis addresses the problem of frequency estimation using low complexity algorithms. One way of achieving such an algorithm is to employ a coarse quantization on the input signal. In this thesis, a 1-bit quantizer is considered which enables the use of low complexity algorithms. Frequency estimation using look-up tables is studied and the properties of such an estimator are presented. By analyzing the look-up tables using the Hadamard transform a novel type of lowcomplexity frequency estimators is proposed. They use operations such as binary multiplication and addition of precalculated constants. This fact makes them suitable in applications where low complexity and high speed are major issues. A hardware demonstrator using the table look-up technique is designed and a prototype is analysed by real measurements. Today, the interest of using digital signal processing instead of analog processing is almost absolute. For example, in testing analog-to-digital converters an important part is to fit a sinewave to the recorded data, as well as to calculate the parameters that in least-squares sense result in the best fit. In this thesis, the sinewave fitting method included in the IEEE Standard 1057 is studied in some detail. Asymptotic Cramér-Rao bounds for three- and four model parameters are derived under the Gaussian assumption. Further, the sinewave fitting properties of the algorithm are analyzed by the parsimony principle. A novel model order selection criterion is proposed for waveform fitting methods in the case of a linear signal model. A generalization of this criterion is made to include the non-linear sinewave fitting application. For multiple sinewave fitting applications two iterative algorithms are proposed. The first method is a combination of the standardized sinewave fit algorithm and the expectation maximization algorithm. The second algorithm is an extension of a single sinewave model to a multiple sinewave model employing the standardized sinewave fitting algorithm. Both algorithms are analysed by numerical means and are shown to accurately resolve multiple sinewaves and produce efficient estimates. Initialization issues of such algorithms are included to some extent.

  • 265.
    Andersson, Tomas
    et al.
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Händel, Peter
    KTH, Superseded Departments, Signals, Sensors and Systems. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    IEEE Standard 1057, Cramér-Rao Bound and the Parsimony Principle2003In: International Workshop on ADC Modelling and Testing, 2003, p. 231-234Conference paper (Refereed)
  • 266.
    Andersson, Tomas
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Robustness of wave-fitting with respect to uncertain parameter values2005In: Instrumentation and Measurement Technology Conference, 2005. IMTC 2005. Proceedings of the IEEE, 2005, Vol. 1, p. 662-665Conference paper (Refereed)
    Abstract [en]

    This paper presents a criterion for model order selection. By usage of the parsimony principle the mean sum-squareerror is evaluated for models subject to imperfections inparameter values. In particular, model imperfections in different sinewavefitting scenarios have been analyzed. The analysis is carried out considering linear models. The obtained result is generalized to models incorporating non-linear parameters. Numerical illustrations are provided in order to gain insight of the behavior of model imperfections, as well as to numerically verify the theoretical results. The main contributions include a general result for linear signal models, as well as some novel results on sinewave-fitting. 

  • 267.
    Andersson, Tomas
    et al.
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Händel, Peter
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Toward a Standardized Multi-Sinewave Fit Algorithm2004In: 9th European Workshop on ADC Modelling and Testing, 2004, Vol. 1, p. 337-342Conference paper (Refereed)
    Abstract [en]

    Multi-sinewave test methods require algorithms for multiple-tone parameter estimation.There exist a vast amount of publications on the topic [1]. This paper presents a generalization ofthe IEEE four-parameter sinewave fit algorithm suitable to handle data comprising multiple sinewaves.The proposed method directly estimates the 3p + 1 parameters of a p-tone model. The algorithmis analyzed numerically with emphasize on its convergence properties and statistical efficiency. Theinitialization of the algorithm is of major importance and an attempt to formulate a proper initializationprocedure is presented.

  • 268.
    Andersson, Tomas
    et al.
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Skoglund, Mikael
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Design of n-channel multiple description vector quantizers2005In: 2005 39th Asilomar Conference on Signals, Systems and Computers, NEW YORK: IEEE , 2005, p. 13-17Conference paper (Refereed)
    Abstract [en]

    A new design approach for multiple description vector quantizers over more than two channels is presented. The design is inspired by the concept of channel optimized vector quantization. While most previous works have split the decoder into several independent entities, identifying the appropriate channel model makes it straightforward to implement the multiple description design problem using only one decoder. Our simulation results compare systems with 2, 4 and 8 channels. We demonstrate significant gains over previous designs, as well as over a benchmark scheme based on separate quantization and forward erasure-correcting error control.

  • 269.
    Andersson, Viktor
    Linköping University, Department of Electrical Engineering, Computer Vision.
    Semantic Segmentation: Using Convolutional Neural Networks and Sparse dictionaries2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The two main bottlenecks using deep neural networks are data dependency and training time. This thesis proposes a novel method for weight initialization of the convolutional layers in a convolutional neural network. This thesis introduces the usage of sparse dictionaries. A sparse dictionary optimized on domain specific data can be seen as a set of intelligent feature extracting filters. This thesis investigates the effect of using such filters as kernels in the convolutional layers in the neural network. How do they affect the training time and final performance?

    The dataset used here is the Cityscapes-dataset which is a library of 25000 labeled road scene images.The sparse dictionary was acquired using the K-SVD method. The filters were added to two different networks whose performance was tested individually. One of the architectures is much deeper than the other. The results have been presented for both networks. The results show that filter initialization is an important aspect which should be taken into consideration while training the deep networks for semantic segmentation.

  • 270.
    Andreasson, Henrik
    et al.
    Örebro University, Örebro, Sweden.
    Bouguerra, Abdelbaki
    Örebro University, Örebro, Sweden.
    Åstrand, Björn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Rögnvaldsson, Thorsteinn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Gold-fish SLAM: An application of SLAM to localize AGVs2014In: Field and Service Robotics: Results of the 8th International Conference / [ed] Kazuya Yoshida & Satoshi Tadokoro, Heidelberg: Springer, 2014, p. 585-598Conference paper (Refereed)
    Abstract [en]

    The main focus of this paper is to present a case study of a SLAM solution for Automated Guided Vehicles (AGVs) operating in real-world industrial environments. The studied solution, called Gold-fish SLAM, was implemented to provide localization estimates in dynamic industrial environments, where there are static landmarks that are only rarely perceived by the AGVs. The main idea of Gold-fish SLAM is to consider the goods that enter and leave the environment as temporary landmarks that can be used in combination with the rarely seen static landmarks to compute online estimates of AGV poses. The solution is tested and verified in a factory of paper using an eight ton diesel-truck retrofitted with an AGV control system running at speeds up to 3m/s. The paper includes also a general discussion on how SLAM can be used in industrial applications with AGVs. © Springer-Verlag Berlin Heidelberg 2014.

  • 271.
    Andres, Bustamante
    et al.
    Tecnológico de Monterrey, MEX.
    Cheddad, Abbas
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Rodriguez-Garcia, Alejandro
    Tecnológico de Monterrey, MEX.
    Digital Image Processing and Development of Machine Learning Models for the Discrimination of Corneal Pathology: An Experimental Model2019Conference paper (Refereed)
  • 272.
    Andreu-Cabedo, Yasmina
    et al.
    University of Central Lancashire, England.
    Castellano, Pedro
    University of Central Lancashire, England.
    Colantonio, Sara
    National Research Council Italy, Italy.
    Coppini, Giuseppe
    National Research Council Italy, Italy.
    Favilla, Riccardo
    National Research Council Italy, Italy.
    Germanese, Danila
    National Research Council Italy, Italy.
    Giannakakis, Giorgos
    Fdn Research and Technology, Greece.
    Giorgi, Daniela
    National Research Council Italy, Italy.
    Larsson, Marcus
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.
    Marraccini, Paolo
    National Research Council Italy, Italy.
    Martinelli, Massimo
    National Research Council Italy, Italy.
    Matuszewski, Bogdan
    University of Central Lancashire, England.
    Milanic, Matijia
    Norvegian University of Science and Technology, Norway.
    Pascali, Mariantonietta
    National Research Council Italy, Italy.
    Pediaditis, Mattew
    Fdn Research and Technology, Greece.
    Raccichini, Giovanni
    National Research Council Italy, Italy.
    Randeberg, Lise
    Norvegian University of Science and Technology, Norway.
    Salvetti, Ovidio
    National Research Council Italy, Italy.
    Strömberg, Tomas
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.
    MIRROR MIRROR ON THE WALL... AN INTELLIGENT MULTISENSORY MIRROR FOR WELL-BEING SELF-ASSESSMENT2015In: 2015 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA and EXPO (ICME), IEEE , 2015Conference paper (Refereed)
    Abstract [en]

    The face reveals the healthy status of an individual, through a combination of physical signs and facial expressions. The project SEMEOTICONS is translating the semeiotic code of the human face into computational descriptors and measures, automatically extracted from videos, images, and 3D scans of the face. SEMEOTICONS is developing a multisensory platform, in the form of a smart mirror, looking for signs related to cardio-metabolic risk. The goal is to enable users to self-monitor their well-being status over time and improve their life-style via tailored user guidance. Building the multisensory mirror requires addressing significant scientific and technological challenges, from touch-less data acquisition, to real-time processing and integration of multimodal data.

  • 273.
    Andrén, Erik
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Simulation and Analysis of Ultrasonic Wave Propagation in Pre-stressed Screws2019Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The use of ultrasound to measure preload in screws and bolts has been studied quite frequently the last decades. The technique is based on establishing a relationship between preload and change in time of flight (TOF) for an ultrasonic pulse propagating back and forth through a screw. This technique has huge advantages compared to other methods such as torque and angle tightening, mainly because of its independence of friction. This is of great interest for Atlas Copco since it increases the accuracy and precision of their assembly tools.

    The purpose of this thesis was to investigate ultrasonic wave propagation in pre-stressed screws using a simulation software, ANSYS, and to analyse the results using signal processing. The simulations were conducted in order to get an understanding about the wavefront distortion effects that arise. Further, an impulse response of the system was estimated with the purpose of dividing the multiple echoes that occur from secondary propagation paths from one other.

    The results strengthen the hypothesis that the received echoes are superpositions of reflections taking different propagation paths through the screw. An analytical estimation of the wavefront curvature also shows that the wavefront distortion due to a higher stress near the screw boundaries can be neglected. Additionally, a compressed sensing technique has been used to estimate the impulse response of the screw. The estimated impulse response models the echoes as superpositions of secondary echoes, with significant taps corresponding to the TOF of the shortest path and a mode-converted echo. The method is also shown to be stable in noisy environments.

    The simulation model gives rise to a slower speed of sound than expected, which most likely is due to the fact that finite element analysis in general overestimates the stiffness of the model.

  • 274. Andrén, Linus
    Active suppression of vibration and noise in industrial applications2004Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Today, active control technology is about to emerge from the research labs into products in various areas. It has become an attractive method where passive techniques have low impact at low frequencies and adding active control to that part is often an attractive solution. The active control technique has been enabled by the rapid development of digital signal processors over the last decades. The focal point in this thesis is active vibration and noise suppression. Two different industrial applications have been subjected to active control to reduce unwanted disturbances. In cutting operations, active vibration suppression has been applied to both external turning and boring operations with successful results. Turning operations, and in particular boring operations, are typical examples of chatter prone machining. In order to implement active vibration control in boring operations a thourough investigation of the boring process has been made in the first two parts in this thesis. The following two parts of the thesis treat active vibration suppression in external turning operations and in boring operations. The second industrial application treats the noise in a fork-lift truck. In the final part of the thesis, active noise suppression has been implemented in the cabin of a fork-lift truck.

  • 275. Andrén, Linus
    et al.
    Håkansson, Lars
    Active Vibration Control of Boring Bar Vibrations2004Report (Other academic)
    Abstract [en]

    The boring operation is a cumbersome manufacturing process plagued by noise and vibration-related problems. A deep internal boring operation in a workpiece is a classic example of chatter-prone machining. The manufacturing industry today is facing tougher tolerances of product surfaces and a desire to process hard-to-cut materials; vibrations must thus be kept to a minimum. An increase in productivity is also interesting from a manufacturing point of view. Penetrating deep and narrow cavities require that the dimensions of the boring bar are long and slender. As a result, the boring bar is inclined to vibrate due to the limited dynamic stiffness. Vibration affects the surface finish, leads to severe noise in the workshop and may also reduce tool life. This report presents an active control solution based on a standard boring bar with an embedded piezo ceramic actuator; this is placed in the area of the peak modal strain energy of the boring bar bending mode to be controlled. An accelerometer is also included in the design; this is mounted as close as possible to the cutting tool. Embedding the electronic parts not only protects them from the harsh environment in a lathe but also enable the design to be used on a general lathe as long as the mounting arrangements are relatively similar. Three different algorithms have been tested in the control system. Since the excitation source of the original vibrations, i.e. the chip formation process cannot be observed directly, the algorithms must be constructed on the basis of a feedback approach. Experimental results from boring operations show that the vibration level can be reduced by 40 dB at the resonance frequency of a fundamental boring bar bending mode; several of its harmonics can also be reduced significantly.

  • 276. Andrén, Linus
    et al.
    Håkansson, Lars
    Brandt, Anders
    Claesson, Ingvar
    Identification of Dynamic Properties of Boring Bar Vibrations in a Continuous Boring Operation2004In: Mechanical systems and signal processing, ISSN 0888-3270, E-ISSN 1096-1216, Vol. 18, no 4, p. 869-901Article in journal (Refereed)
    Abstract [en]

    Vibrations in internal turning operations are usually a cumbersome part of the manufacturing process. This article focuses on the boring bar vibrations. Boring bar vibrations in alloyed steel, stainless steel and cast iron have been measured in both the cutting speed direction and the cutting depth direction with the aid of accelerometers. The dynamic response of a boring bar seem to be a time varying process that exhibits non-linear behaviour. The process is influenced by non-stationary parameters that are not under the control of the operator or experimenter. The vibrations are clearly dominated by the first resonance frequency in one of the two directions of the boring bar. The problem with force modulation in rotary machinery, which appears as side band terms in the spectrum, is also addressed. Furthermore, the resonance frequencies of the boring bar are correlated to an Euler-Bernoulli beam model.

  • 277. Andrén, Linus
    et al.
    Håkansson, Lars
    Brandt, Anders
    Claesson, Ingvar
    Identification of Motion of Cutting Tool Vibration in a Continuous Boring Operation: Correlation to structural Properties2004In: Mechanical systems and signal processing, ISSN 0888-3270, E-ISSN 1096-1216, Vol. 18, no 4, p. 903-27Article in journal (Refereed)
    Abstract [en]

    The internal turning operation has a history of being a cumbersome metal working process as vibration in boring operations is usually inevitable. In this article, the deflection shapes and/or mode shapes as well as the resonance frequencies of a boring bar have been put under scrutiny. Three methods have been used in order to investigate dynamic properties of a clamped boring bar: a theoretical Euler-Bernoulli beam model, an experimental modal analysis and an operating deflection shape analysis. \\ The results indicate a correlation between the shapes of the deflection shapes and/or mode shapes produced by the three different analysis methods. On the other hand, the orientation of the forced deflection shapes and/or mode shapes and the resonance frequencies demonstrates differences between the three methods. During continuous cutting, it is demonstrated that the bending motion of the first two resonance frequencies is to a large extent in the cutting speed direction.

  • 278. Andrén, Linus
    et al.
    Håkansson, Lars
    Claesson, Ingvar
    Active Control of Boring Bar Vibrations Using the Leaky Feedback Filtered X-LMS2003Conference paper (Refereed)
    Abstract [en]

    The boring operation is a cumbersome manufacturing process marred by noise and vibration related problems. The manufacturing industry is having trouble with these kinds of metal cutting operations. There exist several approaches to reduce the vibrations in cutting operations in general. Passive tuned dampers in boring bars have been commercially available for some time. An active solution is likely to be more robust to changes in the spectral content, where the passive counterpart have a small operable area, the active solution is able to adapt to these kinds of changes. Active vibration control in boring operations has been proven to be feasible. The algorithm used in the successful experiments was the feedback filtered X-LMS algorithm. This algorithm does however not guarantee a stable behavior, but incorporating a leakage factor will make the algorithm more robust. Power spectral density of boring bar vibration of real cutting experiments show that the leaky filtered X-LMS algorithm is a possible candidate to be a suitable control algorithm. Nyquist diagrams of the controller during operation show that the stability is increased significantly.

  • 279. Andrén, Linus
    et al.
    Håkansson, Lars
    Claesson, Ingvar
    Active Control of Machine Tool Vibrations in External Turning Operations2003In: Proceedings of the Institution of mechanical engineers. Part B, journal of engineering manufacture, ISSN 0954-4054, E-ISSN 2041-2975, Vol. 217, no 6, p. 869-872Article in journal (Refereed)
    Abstract [en]

    Vibration and noise in metal cutting are ubiquitous problems in the workshop. The external turning operation is one kind of metal cutting that exhibits vibration related problems. Severe noise is also a problem growing in proportion due to regulations in preventing hearing loss. Active vibration control is a potential solution to such problems. With the piezo ceramic actuator technology of today, the size of the actuator can be kept small and still be able to produce a sufficient amount of force for the anti vibrations. Results from several continuous cutting experiments show a 40 dB reduction of the cutting tool vibration level. The design of the active technique enables this technology to be applicable to a general lathe provided the mounting arrangement is fairly similar.

  • 280. Andrén, Linus
    et al.
    Håkansson, Lars
    Claesson, Ingvar
    Actuator placements and Variations in the Control Path estimates in the Active Control of Boring Bar Vibrations2004Conference paper (Refereed)
    Abstract [en]

    A classical example of chatter prone machining is the boring operation. Turning under conditions with high vibrations in the cutting tool deteriorates the surface finish and may cause tool breakage. Severe noise is also a consequence of the high vibration levels in the boring bar. Active control is one possible solution to the noise and vibration problem in boring operations. In boring operations the boring bar usually have vibration components in both the cutting speed and the cutting depth direction. The introduction of the control force in different angles in between the cutting speed and the cutting depth directions have been investigated. Furthermore, control path estimates produced when the active boring bar was not in contact with the workpiece and during continuous cutting operation are compared. Experimental results indicate that the control force should be introduced in the cutting speed direction. Although the vibrations are controlled in just the cutting speed direction the vibrations in the cutting depth direction are also reduced significantly.

  • 281. Andrén, Linus
    et al.
    Håkansson, Lars
    Claesson, Ingvar
    Performance Evaluation of Active Vibration Control of Boring Operations Using Different Active Boring Bars2003Conference paper (Refereed)
    Abstract [en]

    Vibration and noise in boring operations are ubiquitous problems in the workshop. In boring operations, the boring bar is subjected to forces from both the cutting speed and the cutting depth direction. To solve the vibration problem using active techniques would normally require two actuators in order to enable the control of both directions. By mounting one actuator in between the cutting speed and the cutting depth direction it is possible to achieve an active control solution with one actuator. Using only one actuator not only simplifies the control algorithm and saves extra equipment but is also favourable in terms of modifications of the boring bar. The harsh environment in a lathe more or less requires that both sensors and actuators are embedded and sealed into the boring bar. Since the forces that are to be controlled are large, the space needed for the actuator is substantial. Thus using only one actuator will keep the modified boring bar stiffer than a two actuator design. Three boring bars with the actuator mounted at different angles between the cutting speed and the cutting depth directions have been tested. Results from cutting experiments show that the one actuator solution has good potentials to the vibration problem in boring operations.

  • 282. Andrén, Linus
    et al.
    Håkansson, Lars
    Claesson, Ingvar
    Lagö, Thomas L
    Piezo Ceramic Actuators versus High Magnetostrictive Actuators in the Active control of Tool Vibration1999Conference paper (Refereed)
    Abstract [en]

    In the turning operation chatter or vibration is a frequent problem, which affects the result of the machining, and, in particular, the surface finish. Tool life is also influenced by vibration. Severe acoustic noise in the working environment frequently occurs as a result of dynamic motion between the cutting tool and the workpiece. These problems can be reduced by active control of machine-tool vibration. In the active control system for the control of tool vibration a tool holder construction with integrated high magnetostrictive actuators was used. However, high magnetostrictive actuators generally have a non-linear behavior and it is a well known fact that non-linear properties in the forward path in an active control system is likely to degrade the robustness of the control system. A new generation embedded active tool holder shanks based on piezo ceramic actuators has been developed. Based on spectrum estimates, both coherence spectrum and frequency response function estimates has been calculated for both the old tool holder construction and the new generation active tool holder shank. From the results it follows that the phase delay is smaller and the linearity of the new generation active tool holder shank are superior compared to the old technology. The physical features and properties of the new generation active tool holders are superior to the old tool holder.

  • 283. Andrén, Linus
    et al.
    Johansson, Sven
    Winberg, Mathias
    Claesson, Ingvar
    Active Noise Control Experiments in a Fork-lift Truck Cabin2004Conference paper (Refereed)
    Abstract [en]

    High comfort for the driver in working vehicles is an important feature as well as a demand from the drivers. Low noise level is an essential factor for the manufacturer to maintain a high standard and comfort of vehicles. In many cases the noise inside the cabin can be related to the engine orders. Hydraulic pumps and fans are also related to the engine but not necessarily integers of the engine order. Passive absorbers are not suitable for the lowest frequencies and one approach is to use an active noise control system to solve the noise problem at low frequencies. In the present experiment loudspeakers were mounted inside the cabin of a fork lift-truck to produce the secondary noise field. To sense the residual noise, microphones were installed close to the driver's head. The aim is to create a zone of reduced noise around the head. Since a large portion of the noise inside the cabin can be related to the engine, an active control system based on a feedforward solution is possible. Experimental results from a feedforward solution of active noise control in a fork-lift truck cabin show that the noise level in the low frequency region can be reduced significantly.

  • 284.
    Ansari, Yousuf Hameed
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
    Siddiqui, Sohaib Ahmed
    Blekinge Institute of Technology, Faculty of Computing, Department of Communication Systems.
    Quality Assessment for HEVC Encoded Videos: Study of Transmission and Encoding Errors2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    There is a demand for video quality measurements in modern video applications specifically in wireless and mobile communication. In real time video streaming it is experienced that the quality of video becomes low due to different factors such as encoder and transmission errors. HEVC/H.265 is considered as one of the promising codecs for compression of ultra-high definition videos. In this research, full reference based video quality assessment is performed. The raw format reference videos have been taken from Texas database to make test videos data set. The videos are encoded using HM9 reference software in HEVC format. Encoding errors has been set during the encoding process by adjusting the QP values. To introduce packet loss in the video, the real-time environment has been created. Videos are sent from one system to another system over UDP protocol in NETCAT software. Packet loss is induced with different packet loss ratios into the video using NETEM software. After the compilation of video data set, to assess the video quality two kind of analysis has been performed on them. Subjective analysis has been carried on different human subjects. Objective analysis has been achieved by applying five quality matrices PSNR, SSIM, UIQI, VFI and VSNR. The comparison is conducted on the objective measurement scores with the subjective and in the end results deduce from classical correlation methods.

  • 285.
    Antoja Lleonart, Guillem
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    New Generation 4-Channel GNSS Receiver: Design, Production, and Testing2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Due to the current research needs and the lack of commercial multi-channel, multi-constellation GNSS receivers, a two-board solution has been developed so it can be mated with and take advantage of the processing power of the FPGA board branded as MicroZed.

    In order to achieve the proposed goals, an initial phase for assessing and updating the older design, building, and testing of SiGe modules (including both the electronics and casings) has been carried out. The results included demonstrate performances at logging GPS-L1 data with similar C/N0 and AGC values as the previous versions of the modules and offering navigation solutions with accuracies of a few meters. Secondly, a first iteration and design proposal for the new generation receiver has been proposed for GPS and GLONASS L1 and L2, which has been manufactured and tested. Partial tests have been performed due to the flaws of the current revision of the MicroZed Board in regards to its communication peripherals, and the results have validated the receiver’s design provided certain modifications are considered for future iterations. Furthermore, voltage and frequency tests have provided results with an error of less than 7%, and signal tests have provided C/N0 values similar to those of the SiGe modules of around 47[dB-Hz] which will be a useful baseline for future iterations. Finally, a design proposal for an Interface Board used between the older NT1065_PMOD Board and other FPGA boards carrying the standardized FMC connectors has been added to the report and negotiations with manufacturers have been engaged.

  • 286. Aouada, D.
    et al.
    Al Ismaeil, K.
    Idris, K. K.
    Ottersten, Björn
    Surface UP-SR for an improved face recognition using low resolution depth cameras2014In: 2014 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), IEEE conference proceedings, 2014, p. 107-112Conference paper (Refereed)
    Abstract [en]

    We address the limitation of low resolution depth cameras in the context of face recognition. Considering a face as a surface in 3-D, we reformulate the recently proposed Upsampling for Precise Super-Resolution algorithm as a new approach on three dimensional points. This reformulation allows an efficient implementation, and leads to a largely enhanced 3-D face reconstruction. Moreover, combined with a dedicated face detection and representation pipeline, the proposed method provides an improved face recognition system using low resolution depth cameras. We show experimentally that this system increases the face recognition rate as compared to directly using the low resolution raw data.1.

  • 287.
    Apelfröjd, Rikke
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Channel Estimation and Prediction for 5G Applications2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Accurate channel state information (CSI) is important for many candidate techniques of future wireless communication systems. However, acquiring CSI can sometimes be difficult, especially if the user equipment is mobile in which case the future channel realisations must be estimated/predicted. In realistic settings the predictability of radio channels is limited due to measurement noise, limited model orders and since the fading statistics must be modelled based on a set of limited and noisy training data.

    In this thesis, the limits of predictability for the radio channel are investigated. Results show that the predictability is limited primarily due to limitations in the training data, while the model order provides a second order limitation effect and the measurement noise comes in as a third order effect.

    Then, a Kalman-based linear filter is studied for potential 5G technologies:

    Coherent coordinated multipoint joint transmission, where channel predictions and the covariance matrix of the prediction error are used to design a robust linear precoder, evaluated in a three base station system. Results show that prediction improves the CSI for the pedestrian users such that system delays of 10 ms are acceptable. The use of the covariance matrix is important for difficult user groups, but of less importance with a simple user grouping system proposed.

    Massive multiple-input multiple-output (MIMO) in frequency division duplex (FDD) systems were a reduced, suboptimal, Kalman filter is suggested to estimate channels based on non-orthogonal pilots. By introducing a fixed grid of beams, the system generates sparsity in the channel vectors seen by each user, which then estimates its most relevant channels based on unique pilot codes for each beam. Results show that there is a 5 dB loss compared to orthogonal pilots.

    Downlink time division duplex (TDD) channels are estimated based on uplink pilots. By using a predictor antenna, which scouts the channel in advance, the desired downlink channel can be estimated using pilot-based estimates of the channels before and after it (in space). Results indicate that, with the help of Kalman smoothing, predictor antennas can enable accurate CSI for TDD downlinks at vehicular velocities of 80 km/h.

  • 288.
    Apelfröjd, Rikke
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Design Aspects of Coordinated Multipoint Transmission: A Study of Channel Predictions, Resource Allocation, User Grouping and Robust Linear Precoding for Coherent Joint Transmission2014Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Shadowed areas and interference at cell borders pose great challenges for future wireless broadband systems. Coordinated Multipoint (CoMP) coherent joint transmission has shown the potential to overcome these challenges by turning harmful interference into useful signal power. However, there are obstacles to overcome before coherent joint transmission CoMP can be deployed. Some of these are the investigated in this thesis.

    First, coherent joint transmission requires very accurate Channel State Information (CSI), but unfortunately long system latencies cause outdating of the CSI. This can to some extend be counteracted by channel predictions. Two schemes are here investigated for predicting downlink Frequency Division Duplex (FDD) Orthogonal Frequency Division Multiplexing (OFDM) channels; Kalman filters and “predictor antennas”. The first is well suited for slow moving users, e.g. pedestrians or cyclists, as it does not require any special antenna setup. The second, which utilizes an extra antenna, located in front of the main receive antennas, is well suited for vehicular users, such as buses or trams, as these require long spatial prediction horizon.

    Second, a user grouping and resource allocation scheme is investigated. This scheme forms CoMP groups by local resource allocations and provides multi-user diversity gains very close to the optimal gains, found through an extensive combinatorial search. It has very low complexity, requires less feedback capacity than other schemes and places no demands on backhaul capacity.

    Finally, a linear precoder, which is robust to errors in the CSI, is investigated. This precoder takes the covariances of the channel errors into account while optimizing a Mean Squared Error (MSE) criterion. The MSE criterion includes design parameters that can be used as flexible tools for low dimensional searches with respect to an arbitrary optimization criterion, e.g. a weighted sum-rate criterion. The precoder design is also extended to handle backhaul constraints.

    Results show that with the combination of these three schemes: channel predictions, the proposed user grouping and resource allocation scheme and the robust linear precoder, then coherent joint transmission will indeed provide large capacity gains.

  • 289.
    Apelfröjd, Rikke
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Design and measurement based evaluations of coherent JT CoMP: a study of precoding, user grouping and resource allocation using predicted CSI2014In: EURASIP Journal on Wireless Communications and Networking, ISSN 1687-1472, E-ISSN 1687-1499, p. 100-Article in journal (Refereed)
    Abstract [en]

    Coordinated multipoint (CoMP) transmission provides high theoretic gains in spectral efficiency with coherent joint transmission (JT) to multiple users. However, this requires accurate channel state information at the transmitter (CSIT) and also user groups with spatially compatible users. The aim of this paper is to use measured channels to investigate if significant CoMP gains can still be obtained with channel estimation errors. This turns out to be the case, but requires the combination of several techniques. We here focus on coherent downlink JT CoMP to multiple users within a cluster of cooperating base stations. The use of Kalman predictors is investigated to estimate the complex channel gains at the moment of transmission. It is shown that this can provide sufficient CSIT quality for JT CoMP even for long (> 20 ms) system delays at 2.66 GHz at pedestrian velocities or, for lower delays, at 500 MHz, at vehicular velocities. A user grouping and resource allocation scheme that provides appropriate groups for CoMP is also suggested. It provides performance close to that obtained by exhaustive search at very low complexity, low feedback cost and very low backhaul cost. Finally, a robust linear precoder that takes channel uncertainties into account when designing the precoding matrix is considered. We show that, in challenging scenarios, this provides large gains compared with zero-forcing precoding. Evaluations of these design elements are based on measured channels with realistic noise and intercluster interference assumptions. These show that high JT CoMP gains can be expected, on average over large sets of user positions, when the above techniques are combined - especially in severely intracluster interference limited scenarios.

  • 290.
    Apelfröjd, Rikke
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Aronsson, Daniel
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Measurement-based evaluation of robust linear precoding for downlink CoMP2012In: IEEE International Conference on Communications, ICC, Ottawa, Canada, 2012Conference paper (Refereed)
    Abstract [en]

    We study the design and evaluation of joint processing coordinated multipoint (CoMP) downlink transmission. Precoders will then be designed based on outdated channel state information (CSI), so interference cannot be eliminated completely as by an ideal zero-forcing (ZF) solution. We here strive to design and evaluate realistic linear transmit schemes. Kalman predictors are used for orthogonal frequency-division multiplexing (OFDM) channels. They provide optimal linear predictions and also estimates of their uncertainty. Robust linear precoders are designed based on these uncertainty estimates. We introduce and use robust linear quadratic optimal feedforward control, with the criterion averaged (marginalized) over the CSI uncertainty. This flexible solution performs minimum mean square error (MSE) minimization. It can also iteratively optimize other criteria, such as sum-rate. The prediction- and transmission performance is evaluated using measured data on 20 MHz OFDM downlinks from three base stations, for users at fast pedestrian velocities. Downlink CoMP is here also compared to cellular transmission, that uses orthogonal resources within cells but allows uncontrolled interference between cells.

  • 291.
    Apelfröjd, Rikke
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Zirwas, Wolfgang
    Nokia Bell Labs, D-81541 Munich, Germany.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Low-Overhead Cyclic Reference Signals for Channel Estimation in FDD Massive MIMO2019In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 67, no 5, p. 3279-3291Article in journal (Refereed)
    Abstract [en]

    Massive multiple input multiple output (MIMO) transmission and coordinated multipoint transmission are candidate technologies for increasing data throughput in evolving 5G standards. Frequency division duplex (FDD) is likely to remain predominant in large parts of the spectrum below 6 GHz for future 5G systems. Therefore, it is important to estimate the downlink FDD channels from a very large number of antennas, while avoiding an excessive downlink reference signal overhead. We here propose and investigate a three part solution. First, massive MIMO downlinks use a fixed grid of beams. For each user, only a subset of beams will then be relevant, and require estimation. Second, sets of coded reference signal sequences, with cyclic patterns over time, are used. Third, each terminal estimates its most relevant channels. We here propose and compare a linear mean square estimation and a Kalman estimation. Both utilize frequency and antenna correlation, and the later also utilizes temporal correlation. In extensive simulations, this scheme provides channel estimates that lead to an insignificant beamforming performance degradation as compared to full channel knowledge. The cyclic pattern of coded reference signals is found to be important for reliable channel estimation, without having to adjust the reference signals to specific users.

  • 292.
    Appilla Chakravarthula, Rohan
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
    Veluru, Chaithanya Kumar Reddy
    Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
    Intelligent Beam Weight Computation for Massive Beamforming2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    LTE (Long Term Evolution) is likely the most complex wireless system ever developed. It incorporates features that could not have been economically implemented as recently as a decade ago. Today, with large-scale ICs, LTE can be easily accommodated in base stations and battery-powered handsets alike. LTE-Advanced is the upgraded version of LTE technology for providing more speed and greater reliability.

    In this report, the wireless communication between the user and base station is implemented by creating 4G LTE environment in MATLAB. Impact of Coherence time on beam weight computation varies for different delay profiles. Moreover, SNR of the transmitted signal varies significantly by the time gap between two successive uplink frames in TDD configuration. In this report, computationally efficient algorithm for reducing beam weight computations in system level LTE simulations is proposed.

    The wireless channel is modelled in both Rician and Rayleigh fading channel. Efficiency of beam forming algorithms is observed at different channel conditions like delay profile, fading channel, bandwidth, correlation, modulation technique.

    The MUSIC algorithm is implemented for detecting the movement of the users in Line of sight condition

  • 293. Aravanis, Alexis
    et al.
    Shankar Bhavani, M.R.
    Danoy, Gregoire
    Arapoglou, Pantelis-Daniel
    Cottis, Panayotis
    Ottersten, Björn
    Multi-objective Optimization Approach to Power Allocation in Multibeam Systems2012Conference paper (Refereed)
  • 294. Aravanis, Alexis
    et al.
    Shankar Bhavani, M.R.
    Danoy, Gregoire
    Arapoglou, Pantelis-Daniel
    Cottis, Panayotis
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Power allocation in multibeam satellites: A hybrid-genetic algorithm approach2012Conference paper (Refereed)
  • 295.
    Ardeshiri, Tohid
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Analytical Approximations for Bayesian Inference2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Bayesian inference is a statistical inference technique in which Bayes’ theorem is used to update the probability distribution of a random variable using observations. Except for few simple cases, expression of such probability distributions using compact analytical expressions is infeasible. Approximation methods are required to express the a priori knowledge about a random variable in form of prior distributions. Further approximations are needed to compute posterior distributions of the random variables using the observations. When the computational complexity of representation of such posteriors increases over time as in mixture models, approximations are required to reduce the complexity of such representations.

    This thesis further extends existing approximation methods for Bayesian inference, and generalizes the existing approximation methods in three aspects namely; prior selection, posterior evaluation given the observations and maintenance of computation complexity.

    Particularly, the maximum entropy properties of the first-order stable spline kernel for identification of linear time-invariant stable and causal systems are shown. Analytical approximations are used to express the prior knowledge about the properties of the impulse response of a linear time-invariant stable and causal system.

    Variational Bayes (VB) method is used to compute an approximate posterior in two inference problems. In the first problem, an approximate posterior for the state smoothing problem for linear statespace models with unknown and time-varying noise covariances is proposed. In the second problem, the VB method is used for approximate inference in state-space models with skewed measurement noise.

    Moreover, a novel approximation method for Bayesian inference is proposed. The proposed Bayesian inference technique is based on Taylor series approximation of the logarithm of the likelihood function. The proposed approximation is devised for the case where the prior distribution belongs to the exponential family of distributions.

    Finally, two contributions are dedicated to the mixture reduction (MR) problem. The first contribution, generalize the existing MR algorithms for Gaussian mixtures to the exponential family of distributions and compares them in an extended target tracking scenario. The second contribution, proposes a new Gaussian mixture reduction algorithm which minimizes the reverse Kullback-Leibler divergence and has specific peak preserving properties.

  • 296.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Nurminen, Henri
    Department of Automation Science and Engineering, Tampere University of Technology, Finland.
    Pichè, Robert
    Department of Automation Science and Engineering, Tampere University of Technology, Finland.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Variational Iterations for Filtering and Smoothing with skew-t measurement noise2015Report (Other academic)
    Abstract [en]

    In this technical report, some derivations for the filter and smoother proposed in [1] are presented. More specifically, the derivations for the cyclic iteration needed to solve the variational Bayes filter and smoother for state space models with skew t likelihood proposed in [1] are presented.

  • 297.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Orguner, Umut
    Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Bayesian Inference via Approximation of Log-likelihood for Priors in Exponential FamilyManuscript (preprint) (Other academic)
    Abstract [en]

    In this paper, a Bayesian inference technique based on Taylor series approximation of the logarithm of the likelihood function is presented. The proposed approximation is devised for the case where the prior distribution belongs to the exponential family of distributions. The logarithm of the likelihood function is linearized with respect to the sufficient statistic of the prior distribution in exponential family such that the posterior obtains the same exponential family form as the prior. Similarities between the proposed method and the extended Kalman filter for nonlinear filtering are illustrated. Further, an extended target measurement update for target models where the target extent is represented by a random matrix having an inverse Wishart distribution is derived. The approximate update covers the important case where the spread of measurement is due to the target extent as well as the measurement noise in the sensor.

  • 298.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Orguner, Umut
    Middle East Technical University.
    Lundquist, Christian
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Schön, Thomas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    On mixture reduction for multiple target tracking2012Conference paper (Refereed)
  • 299.
    Ardeshiri, Tohid
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Orguner, Umut
    Özkan, Emre
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Gaussian Mixture Reduction Using Reverse Kullback-Leibler DivergenceManuscript (preprint) (Other academic)
  • 300.
    Ardeshiri, Tohid
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control.
    Özkan, Emre
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    An adaptive PHD filter for tracking with unknown sensor characteristics2013Conference paper (Refereed)
    Abstract [en]

    In multi-target tracking, the discrepancy between the nominal and the true values of the model parameters might result in poor performance. In this paper, an adaptive Probability Hypothesis Density (PHD) filter is proposed which accounts for sensor parameter uncertainty. Variational Bayes technique is used for approximate inference which provides analytic expressions for the PHD recursions analogous to the Gaussian mixture implementation of the PHD filter. The proposed method is evaluated in a multi-target tracking scenario. The improvement in the performance is shown in simulations.

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