Download or read book Sequential Monte Carlo Methods with Applications to Positioning and Tracking in Wireless Networks written by Svetlana Bizjajeva and published by . This book was released on 2008 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Introduction to Sequential Monte Carlo written by Nicolas Chopin and published by Springer Nature. This book was released on 2020-10-01 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a general introduction to Sequential Monte Carlo (SMC) methods, also known as particle filters. These methods have become a staple for the sequential analysis of data in such diverse fields as signal processing, epidemiology, machine learning, population ecology, quantitative finance, and robotics. The coverage is comprehensive, ranging from the underlying theory to computational implementation, methodology, and diverse applications in various areas of science. This is achieved by describing SMC algorithms as particular cases of a general framework, which involves concepts such as Feynman-Kac distributions, and tools such as importance sampling and resampling. This general framework is used consistently throughout the book. Extensive coverage is provided on sequential learning (filtering, smoothing) of state-space (hidden Markov) models, as this remains an important application of SMC methods. More recent applications, such as parameter estimation of these models (through e.g. particle Markov chain Monte Carlo techniques) and the simulation of challenging probability distributions (in e.g. Bayesian inference or rare-event problems), are also discussed. The book may be used either as a graduate text on Sequential Monte Carlo methods and state-space modeling, or as a general reference work on the area. Each chapter includes a set of exercises for self-study, a comprehensive bibliography, and a “Python corner,” which discusses the practical implementation of the methods covered. In addition, the book comes with an open source Python library, which implements all the algorithms described in the book, and contains all the programs that were used to perform the numerical experiments.
Download or read book Sequential Monte Carlo Methods in Practice written by Arnaud Doucet and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo methods are revolutionizing the on-line analysis of data in many fileds. They have made it possible to solve numerically many complex, non-standard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques.
Download or read book Advanced Sequential Monte Carlo Methods and Their Applications to Sparse Sensor Network for Detection and Estimation written by Kai Kang and published by . This book was released on 2016 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: The general state space models present a flexible framework for modeling dynamic systems and therefore have vast applications in many disciplines such as engineering, economics, biology, etc. However, optimal estimation problems of non-linear non-Gaussian state space models are analytically intractable in general. Sequential Monte Carlo (SMC) methods become a very popular class of simulation-based methods for the solution of optimal estimation problems. The advantages of SMC methods in comparison with classical filtering methods such as Kalman Filter and Extended Kalman Filter are that they are able to handle non-linear non-Gaussian scenarios without relying on any local linearization techniques. In this thesis, we present an advanced SMC method and the study of its asymptotic behavior. We apply the proposed SMC method in a target tracking problem using different observation models. Specifically, a distributed SMC algorithm is developed for a wireless sensor network (WSN) that incorporates with an informative-sensor detection technique. The novel SMC algorithm is designed to surmount the degeneracy problem by employing a multilevel Markov chain Monte Carlo (MCMC) procedure constructed by engaging drift homotopy and likelihood bridging techniques. The observations are gathered only from the informative sensors, which are sensing useful observations of the nearby moving targets. The detection of those informative sensors, which are typically a small portion of the WSN, is taking place by using a sparsity-aware matrix decomposition technique. Simulation results showcase that our algorithm outperforms current popular tracking algorithms such as bootstrap filter and auxiliary particle filter in many scenarios.
Download or read book Mobile Positioning and Tracking written by Simone Frattasi and published by John Wiley & Sons. This book was released on 2017-07-21 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential guide to state-of-the art mobile positioning and tracking techniques—fully updated for new and emerging trends in the field Mobile Positioning and Tracking, Second Edition explores state-of-the-art mobile positioning solutions applied on top of current wireless communication networks. Application areas covered include positioning, data fusion and filtering, tracking, error mitigation, both conventional and cooperative positioning technologies and systems, and more. The authors fill the gap between positioning and communication systems, showing how features of wireless communications systems can be used for positioning purposes and how the retrieved location information can be used to enhance the performance of wireless networks. Unlike other books on the subject, Mobile Positioning and Tracking: From Conventional to Cooperative Techniques, 2nd Edition covers the entire positioning and tracking value chain, starting from the measurement of positioning signals, and offering valuable insights into the theoretical fundamentals behind these methods and how they relate to application areas such as location-based services, as well as related disciplines and professional concerns, including global business considerations and the changing laws and standards governing wireless communication networks. Fully updated and revised for the latest developments in the field, this Second Edition: Features new chapters on UWB positioning and tracking, indoor positioning in WLAN, and multi-tag positioning in RFID Explores an array of positioning and tracking systems based on satellite and terrestrial systems technologies and methods Introduces advanced and novel topics such as localisation in heterogeneous and cooperative scenarios Provides a bridge between research and industry with potential implementations of the solutions presented Mobile positioning and tracking is subject to continuous innovations and improvements. This important working resource helps busy industry professionals and practitioners—including software and service developers—stay on top of emerging trends in the field. It is also a valuable reference for advanced students in related disciplines studying positioning and mobile technologies.
Download or read book Mobile Positioning and Tracking written by João Figueiras and published by John Wiley & Sons. This book was released on 2011-07-05 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the most recent state of the art in mobile positioning and tracking techniques. This book discusses mobile positioning solutions applied on top of current wireless communication networks. In addition, the authors introduce advanced and novel topics such as localization in heterogeneous and cooperative networks, providing a unified treatment of the topic for researchers and industry professionals alike. Furthermore, the book focuses on application areas of positioning, basics of wireless communications for positioning, data fusion and filtering techniques, fundamentals of tracking, error mitigation techniques, positioning systems and technologies, and cooperative mobile positioning systems. Key Features: Covers the state of the art of satellite- and terrestrial-based positioning systems, spanning from outdoor to indoor environments and from wide area networks to short-range networks Discusses a whole range of topics related to mobile positioning: from fundamentals of positioning to the description of a wide spectrum of mobility models for tracking, from details on data fusion and filtering techniques to error mitigation techniques (including aspects of signal processing) Provides a solid bridge between research and industry envisaging a potential implementation of the presented solutions Fills the gap between positioning and communication systems, showing how features of communication systems can be used for positioning purposes and how the retrieved location information can be used to enhance the performance of wireless networks. Includes an accompanying website This book will be a valuable guide for advanced students studying related courses. Professionals and practitioners in the field of positioning and mobile technologies, and software and service developers will also find this book of interest.
Download or read book WLAN Positioning Systems written by Azadeh Kushki and published by Cambridge University Press. This book was released on 2012-01-26 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes the relevant detection and estimation theory, sets out key design challenges and examines practical design trade-offs and experimental results.
Download or read book Positioning in Wireless Communications Systems written by Stephan Sand and published by John Wiley & Sons. This book was released on 2014-05-05 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Positioning in Wireless Communications Systems explains the principal differences and similarities of wireless communications systems and navigation systems. It discusses scenarios which are critical for dedicated navigation systems such as the Global Positioning System (GPS) and which motivate the use of positioning based on terrestrial wireless communication systems. The book introduces approaches for determination of parameters which are dependent on the position of the mobile terminal and also discusses iterative algorithms to estimate and track the position of the mobile terminal. Models for radio propagation and user mobility are important for performance investigations and assessments using computer simulations. Thus, channel and mobility models are explored, especially focussing on critical navigation environments like urban or indoor scenarios. Positioning in Wireless Communications Systems examines advanced algorithms such as hybrid data fusion of satellite navigation and positioning with wireless communications and cooperative positioning among mobile terminals.. The performance of the discussed positioning techniques are explored on the basis of already existing and operable terrestrial wireless communication systems such as GSM, UMTS, or LTE and it is shown how positioning issues are fixed in respective standards. Written by industry experts working at the cutting edge of technological development, the authors are well placed to give an excellent view on this topic, enabling in-depth coverage of current developments. Key features • Unique in its approach to dealing with a heterogeneous system approach, different cell structures and signal proposals for future communications systems • Covers hybrid positioning investigating how GNSS and wireless communications positioning complement each other • Applications and exploitation of positioning information are discussed to show the benefits of including this information in several parts of a wireless communications system
Download or read book Fast Sequential Monte Carlo Methods for Counting and Optimization written by Reuven Y. Rubinstein and published by John Wiley & Sons. This book was released on 2013-11-13 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive account of the theory and application of Monte Carlo methods Based on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for Counting and Optimization is a complete illustration of fast sequential Monte Carlo techniques. The book provides an accessible overview of current work in the field of Monte Carlo methods, specifically sequential Monte Carlo techniques, for solving abstract counting and optimization problems. Written by authorities in the field, the book places emphasis on cross-entropy, minimum cross-entropy, splitting, and stochastic enumeration. Focusing on the concepts and application of Monte Carlo techniques, Fast Sequential Monte Carlo Methods for Counting and Optimization includes: Detailed algorithms needed to practice solving real-world problems Numerous examples with Monte Carlo method produced solutions within the 1-2% limit of relative error A new generic sequential importance sampling algorithm alongside extensive numerical results An appendix focused on review material to provide additional background information Fast Sequential Monte Carlo Methods for Counting and Optimization is an excellent resource for engineers, computer scientists, mathematicians, statisticians, and readers interested in efficient simulation techniques. The book is also useful for upper-undergraduate and graduate-level courses on Monte Carlo methods.
Download or read book On the Applicability of Sequential Monte Carlo Methods to Multiple Target Tracking written by Martin Spengler and published by . This book was released on 2005 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Monte Carlo Methods written by Adrian Barbu and published by Springer Nature. This book was released on 2020-02-24 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book seeks to bridge the gap between statistics and computer science. It provides an overview of Monte Carlo methods, including Sequential Monte Carlo, Markov Chain Monte Carlo, Metropolis-Hastings, Gibbs Sampler, Cluster Sampling, Data Driven MCMC, Stochastic Gradient descent, Langevin Monte Carlo, Hamiltonian Monte Carlo, and energy landscape mapping. Due to its comprehensive nature, the book is suitable for developing and teaching graduate courses on Monte Carlo methods. To facilitate learning, each chapter includes several representative application examples from various fields. The book pursues two main goals: (1) It introduces researchers to applying Monte Carlo methods to broader problems in areas such as Computer Vision, Computer Graphics, Machine Learning, Robotics, Artificial Intelligence, etc.; and (2) it makes it easier for scientists and engineers working in these areas to employ Monte Carlo methods to enhance their research.
Download or read book Sequential Monte Carlo Methods for Nonlinear Discrete Time Filtering written by Marcelo G. and published by Springer Nature. This book was released on 2022-06-01 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: In these notes, we introduce particle filtering as a recursive importance sampling method that approximates the minimum-mean-square-error (MMSE) estimate of a sequence of hidden state vectors in scenarios where the joint probability distribution of the states and the observations is non-Gaussian and, therefore, closed-form analytical expressions for the MMSE estimate are generally unavailable. We begin the notes with a review of Bayesian approaches to static (i.e., time-invariant) parameter estimation. In the sequel, we describe the solution to the problem of sequential state estimation in linear, Gaussian dynamic models, which corresponds to the well-known Kalman (or Kalman-Bucy) filter. Finally, we move to the general nonlinear, non-Gaussian stochastic filtering problem and present particle filtering as a sequential Monte Carlo approach to solve that problem in a statistically optimal way. We review several techniques to improve the performance of particle filters, including importance function optimization, particle resampling, Markov Chain Monte Carlo move steps, auxiliary particle filtering, and regularized particle filtering. We also discuss Rao-Blackwellized particle filtering as a technique that is particularly well-suited for many relevant applications such as fault detection and inertial navigation. Finally, we conclude the notes with a discussion on the emerging topic of distributed particle filtering using multiple processors located at remote nodes in a sensor network. Throughout the notes, we often assume a more general framework than in most introductory textbooks by allowing either the observation model or the hidden state dynamic model to include unknown parameters. In a fully Bayesian fashion, we treat those unknown parameters also as random variables. Using suitable dynamic conjugate priors, that approach can be applied then to perform joint state and parameter estimation. Table of Contents: Introduction / Bayesian Estimation of Static Vectors / The Stochastic Filtering Problem / Sequential Monte Carlo Methods / Sampling/Importance Resampling (SIR) Filter / Importance Function Selection / Markov Chain Monte Carlo Move Step / Rao-Blackwellized Particle Filters / Auxiliary Particle Filter / Regularized Particle Filters / Cooperative Filtering with Multiple Observers / Application Examples / Summary
Download or read book Position Navigation and Timing Technologies in the 21st Century written by Y. Jade Morton and published by John Wiley & Sons. This book was released on 2021-01-13 with total page 902 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers the latest developments in PNT technologies, including integrated satellite navigation, sensor systems, and civil applications Featuring sixty-four chapters that are divided into six parts, this two-volume work provides comprehensive coverage of the state-of-the-art in satellite-based position, navigation, and timing (PNT) technologies and civilian applications. It also examines alternative navigation technologies based on other signals-of-opportunity and sensors and offers a comprehensive treatment on integrated PNT systems for consumer and commercial applications. Volume 1 of Position, Navigation, and Timing Technologies in the 21st Century: Integrated Satellite Navigation, Sensor Systems, and Civil Applications contains three parts and focuses on the satellite navigation systems, technologies, and engineering and scientific applications. It starts with a historical perspective of GPS development and other related PNT development. Current global and regional navigation satellite systems (GNSS and RNSS), their inter-operability, signal quality monitoring, satellite orbit and time synchronization, and ground- and satellite-based augmentation systems are examined. Recent progresses in satellite navigation receiver technologies and challenges for operations in multipath-rich urban environment, in handling spoofing and interference, and in ensuring PNT integrity are addressed. A section on satellite navigation for engineering and scientific applications finishes off the volume. Volume 2 of Position, Navigation, and Timing Technologies in the 21st Century: Integrated Satellite Navigation, Sensor Systems, and Civil Applications consists of three parts and addresses PNT using alternative signals and sensors and integrated PNT technologies for consumer and commercial applications. It looks at PNT using various radio signals-of-opportunity, atomic clock, optical, laser, magnetic field, celestial, MEMS and inertial sensors, as well as the concept of navigation from Low-Earth Orbiting (LEO) satellites. GNSS-INS integration, neuroscience of navigation, and animal navigation are also covered. The volume finishes off with a collection of work on contemporary PNT applications such as survey and mobile mapping, precision agriculture, wearable systems, automated driving, train control, commercial unmanned aircraft systems, aviation, and navigation in the unique Arctic environment. In addition, this text: Serves as a complete reference and handbook for professionals and students interested in the broad range of PNT subjects Includes chapters that focus on the latest developments in GNSS and other navigation sensors, techniques, and applications Illustrates interconnecting relationships between various types of technologies in order to assure more protected, tough, and accurate PNT Position, Navigation, and Timing Technologies in the 21st Century: Integrated Satellite Navigation, Sensor Systems, and Civil Applications will appeal to all industry professionals, researchers, and academics involved with the science, engineering, and applications of position, navigation, and timing technologies. pnt21book.com
Download or read book Handbook of Sensor Networking written by John R. Vacca and published by CRC Press. This book was released on 2015-01-13 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook provides a complete professional reference and practitioner's guide to today's advanced sensor networking technologies. It focuses on both established and recent sensor networking theory, technology, and practice. Specialists at the forefront of the field address immediate and long-term challenges and explore practical solutions to a wide range of sensor networking issues. The book covers the hardware of sensor networks, wireless communication protocols, sensor networks software and architectures, wireless information networks, data manipulation, signal processing, localization, and object tracking through sensor networks.
Download or read book Sequential Monte Carlo Methods for Nonlinear Discrete time Filtering written by Marcelo G. S. Bruno and published by Morgan & Claypool Publishers. This book was released on 2013 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: In these notes, we introduce particle filtering as a recursive importance sampling method that approximates the minimum-mean-square-error (MMSE) estimate of a sequence of hidden state vectors in scenarios where the joint probability distribution of the states and the observations is non-Gaussian and, therefore, closed-form analytical expressions for the MMSE estimate are generally unavailable. We begin the notes with a review of Bayesian approaches to static (i.e., time-invariant) parameter estimation. In the sequel, we describe the solution to the problem of sequential state estimation in linear, Gaussian dynamic models, which corresponds to the well-known Kalman (or Kalman-Bucy) filter. Finally, we move to the general nonlinear, non-Gaussian stochastic filtering problem and present particle filtering as a sequential Monte Carlo approach to solve that problem in a statistically optimal way. We review several techniques to improve the performance of particle filters, including importance function optimization, particle resampling, Markov Chain Monte Carlo move steps, auxiliary particle filtering, and regularized particle filtering. We also discuss Rao-Blackwellized particle filtering as a technique that is particularly well-suited for many relevant applications such as fault detection and inertial navigation. Finally, we conclude the notes with a discussion on the emerging topic of distributed particle filtering using multiple processors located at remote nodes in a sensor network. Throughout the notes, we often assume a more general framework than in most introductory textbooks by allowing either the observation model or the hidden state dynamic model to include unknown parameters. In a fully Bayesian fashion, we treat those unknown parameters also as random variables. Using suitable dynamic conjugate priors, that approach can be applied then to perform joint state and parameter estimation.
Download or read book Advances in Intelligent Signal Processing and Data Mining written by Petia Georgieva and published by Springer. This book was released on 2012-07-27 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters, Rao Blackwellization, to the biologically inspired paradigm of Neural Networks and decomposition techniques such as Empirical Mode Decomposition, Independent Component Analysis and Singular Spectrum Analysis. The book is directed to the research students, professors, researchers and practitioners interested in exploring the advanced techniques in intelligent signal processing and data mining paradigms.
Download or read book Localization in Wireless Networks written by Jessica Feng Sanford and published by Springer Science & Business Media. This book was released on 2012-05-03 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a computational tour-de-force, this volume wipes away a host of problems related to location discovery in wireless ad-hoc sensor networks. WASNs have recognized potential in many applications that are location-dependent, yet are heavily constrained by factors such as cost and energy consumption. Their “ad-hoc” nature, with direct rather than mediated connections between a network of wireless devices, adds another layer of difficulty. Basing this work entirely on data-driven, coordinated algorithms, the author’s aim is to present location discovery techniques that are highly accurate—and which fit user criteria. The research deploys nonparametric statistical methods and relies on the concept of joint probability to construct error (including location error) models and environmental field models. It also addresses system issues such as the broadcast and scheduling of the beacon. Reporting an impressive accuracy gain of almost 17 percent, and organized in a clear, sequential manner, this book represents a stride forward in wireless localization.
