Beyond the Kalman Filter: Particle Filters for Tracking Applications

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Author :
Publisher : Artech House
ISBN 13 : 9781580538510
Total Pages : 328 pages
Book Rating : 4.5/5 (385 download)

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Book Synopsis Beyond the Kalman Filter: Particle Filters for Tracking Applications by : Branko Ristic

Download or read book Beyond the Kalman Filter: Particle Filters for Tracking Applications written by Branko Ristic and published by Artech House. This book was released on 2003-12-01 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: For most tracking applications the Kalman filter is reliable and efficient, but it is limited to a relatively restricted class of linear Gaussian problems. To solve problems beyond this restricted class, particle filters are proving to be dependable methods for stochastic dynamic estimation. Packed with 867 equations, this cutting-edge book introduces the latest advances in particle filter theory, discusses their relevance to defense surveillance systems, and examines defense-related applications of particle filters to nonlinear and non-Gaussian problems. With this hands-on guide, you can develop more accurate and reliable nonlinear filter designs and more precisely predict the performance of these designs. You can also apply particle filters to tracking a ballistic object, detection and tracking of stealthy targets, tracking through the blind Doppler zone, bi-static radar tracking, passive ranging (bearings-only tracking) of maneuvering targets, range-only tracking, terrain-aided tracking of ground vehicles, and group and extended object tracking.

An Introduction to Sequential Monte Carlo

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Publisher : Springer Nature
ISBN 13 : 3030478459
Total Pages : 378 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis An Introduction to Sequential Monte Carlo by : Nicolas Chopin

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.

Particle Filter Retrofit for All Diesel Engines

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Author :
Publisher : expert verlag
ISBN 13 : 9783816928508
Total Pages : 462 pages
Book Rating : 4.9/5 (285 download)

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Book Synopsis Particle Filter Retrofit for All Diesel Engines by : Andreas Mayer

Download or read book Particle Filter Retrofit for All Diesel Engines written by Andreas Mayer and published by expert verlag. This book was released on 2008 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Particle Filter

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Author :
Publisher : One Billion Knowledgeable
ISBN 13 :
Total Pages : 91 pages
Book Rating : 4.:/5 (661 download)

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Book Synopsis Particle Filter by : Fouad Sabry

Download or read book Particle Filter written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2024-05-13 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is Particle Filter Particle filters, or sequential Monte Carlo methods, are a set of Monte Carlo algorithms used to find approximate solutions for filtering problems for nonlinear state-space systems, such as signal processing and Bayesian statistical inference. The filtering problem consists of estimating the internal states in dynamical systems when partial observations are made and random perturbations are present in the sensors as well as in the dynamical system. The objective is to compute the posterior distributions of the states of a Markov process, given the noisy and partial observations. The term "particle filters" was first coined in 1996 by Pierre Del Moral about mean-field interacting particle methods used in fluid mechanics since the beginning of the 1960s. The term "Sequential Monte Carlo" was coined by Jun S. Liu and Rong Chen in 1998. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Particle filter Chapter 2: Importance sampling Chapter 3: Point process Chapter 4: Fokker-Planck equation Chapter 5: Wiener's lemma Chapter 6: Klein-Kramers equation Chapter 7: Mean-field particle methods Chapter 8: Dirichlet kernel Chapter 9: Generalized Pareto distribution Chapter 10: Superprocess (II) Answering the public top questions about particle filter. (III) Real world examples for the usage of particle filter in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Particle Filter.

Bayesian Signal Processing

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Publisher : John Wiley & Sons
ISBN 13 : 1119125472
Total Pages : 638 pages
Book Rating : 4.1/5 (191 download)

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Book Synopsis Bayesian Signal Processing by : James V. Candy

Download or read book Bayesian Signal Processing written by James V. Candy and published by John Wiley & Sons. This book was released on 2016-06-20 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents the Bayesian approach to statistical signal processing for a variety of useful model sets This book aims to give readers a unified Bayesian treatment starting from the basics (Baye’s rule) to the more advanced (Monte Carlo sampling), evolving to the next-generation model-based techniques (sequential Monte Carlo sampling). This next edition incorporates a new chapter on “Sequential Bayesian Detection,” a new section on “Ensemble Kalman Filters” as well as an expansion of Case Studies that detail Bayesian solutions for a variety of applications. These studies illustrate Bayesian approaches to real-world problems incorporating detailed particle filter designs, adaptive particle filters and sequential Bayesian detectors. In addition to these major developments a variety of sections are expanded to “fill-in-the gaps” of the first edition. Here metrics for particle filter (PF) designs with emphasis on classical “sanity testing” lead to ensemble techniques as a basic requirement for performance analysis. The expansion of information theory metrics and their application to PF designs is fully developed and applied. These expansions of the book have been updated to provide a more cohesive discussion of Bayesian processing with examples and applications enabling the comprehension of alternative approaches to solving estimation/detection problems. The second edition of Bayesian Signal Processing features: “Classical” Kalman filtering for linear, linearized, and nonlinear systems; “modern” unscented and ensemble Kalman filters: and the “next-generation” Bayesian particle filters Sequential Bayesian detection techniques incorporating model-based schemes for a variety of real-world problems Practical Bayesian processor designs including comprehensive methods of performance analysis ranging from simple sanity testing and ensemble techniques to sophisticated information metrics New case studies on adaptive particle filtering and sequential Bayesian detection are covered detailing more Bayesian approaches to applied problem solving MATLAB® notes at the end of each chapter help readers solve complex problems using readily available software commands and point out other software packages available Problem sets included to test readers’ knowledge and help them put their new skills into practice Bayesian Signal Processing, Second Edition is written for all students, scientists, and engineers who investigate and apply signal processing to their everyday problems.

Particle Filters for Random Set Models

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Publisher : Springer Science & Business Media
ISBN 13 : 1461463165
Total Pages : 184 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Particle Filters for Random Set Models by : Branko Ristic

Download or read book Particle Filters for Random Set Models written by Branko Ristic and published by Springer Science & Business Media. This book was released on 2013-04-15 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses state estimation of stochastic dynamic systems from noisy measurements, specifically sequential Bayesian estimation and nonlinear or stochastic filtering. The class of solutions presented in this book is based on the Monte Carlo statistical method. Although the resulting algorithms, known as particle filters, have been around for more than a decade, the recent theoretical developments of sequential Bayesian estimation in the framework of random set theory have provided new opportunities which are not widely known and are covered in this book. This book is ideal for graduate students, researchers, scientists and engineers interested in Bayesian estimation.

Introduction to Bayesian Tracking and Particle Filters

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Publisher : Springer Nature
ISBN 13 : 3031322428
Total Pages : 124 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Introduction to Bayesian Tracking and Particle Filters by : Lawrence D. Stone

Download or read book Introduction to Bayesian Tracking and Particle Filters written by Lawrence D. Stone and published by Springer Nature. This book was released on 2023-05-31 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a quick but insightful introduction to Bayesian tracking and particle filtering for a person who has some background in probability and statistics and wishes to learn the basics of single-target tracking. It also introduces the reader to multiple target tracking by presenting useful approximate methods that are easy to implement compared to full-blown multiple target trackers. The book presents the basic concepts of Bayesian inference and demonstrates the power of the Bayesian method through numerous applications of particle filters to tracking and smoothing problems. It emphasizes target motion models that incorporate knowledge about the target’s behavior in a natural fashion rather than assumptions made for mathematical convenience. The background provided by this book allows a person to quickly become a productive member of a project team using Bayesian filtering and to develop new methods and techniques for problems the team may face.

Macroeconometrics and Time Series Analysis

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Publisher : Springer
ISBN 13 : 0230280838
Total Pages : 417 pages
Book Rating : 4.2/5 (32 download)

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Book Synopsis Macroeconometrics and Time Series Analysis by : Steven Durlauf

Download or read book Macroeconometrics and Time Series Analysis written by Steven Durlauf and published by Springer. This book was released on 2016-04-30 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.

Optimal State Estimation

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Publisher : John Wiley & Sons
ISBN 13 : 0470045337
Total Pages : 554 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Optimal State Estimation by : Dan Simon

Download or read book Optimal State Estimation written by Dan Simon and published by John Wiley & Sons. This book was released on 2006-06-19 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering. While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed learning: * Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimation * Simple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practice * MATLAB(r)-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parameters Armed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H? filtering. Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries.

Diesel Particulate Filter Technology

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Publisher : SAE International
ISBN 13 : 0768017076
Total Pages : 374 pages
Book Rating : 4.7/5 (68 download)

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Book Synopsis Diesel Particulate Filter Technology by : Timothy V Johnson

Download or read book Diesel Particulate Filter Technology written by Timothy V Johnson and published by SAE International. This book was released on 2007-03-28 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Until recently, the complexity of the Diesel Particulate Filter (DPF) system has hindered its commercial success. Stringent regulations of diesel emissions has lead to advancements in this technology, therefore mainstreaming the use of DPFs in light- and heavy-duty diesel filtration applications. This book covers the latest and most important research in DPF systems, focusing mainly on the advancements of the years 2002-2006. Editor Timothy V. Johnson selected the top 29 SAE papers covering the most significant research in this technology.

Image Processing

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Publisher : John Wiley & Sons
ISBN 13 : 0471745782
Total Pages : 454 pages
Book Rating : 4.4/5 (717 download)

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Book Synopsis Image Processing by : Tinku Acharya

Download or read book Image Processing written by Tinku Acharya and published by John Wiley & Sons. This book was released on 2005-10-03 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image processing-from basics to advanced applications Learn how to master image processing and compression with this outstanding state-of-the-art reference. From fundamentals to sophisticated applications, Image Processing: Principles and Applications covers multiple topics and provides a fresh perspective on future directions and innovations in the field, including: * Image transformation techniques, including wavelet transformation and developments * Image enhancement and restoration, including noise modeling and filtering * Segmentation schemes, and classification and recognition of objects * Texture and shape analysis techniques * Fuzzy set theoretical approaches in image processing, neural networks, etc. * Content-based image retrieval and image mining * Biomedical image analysis and interpretation, including biometric algorithms such as face recognition and signature verification * Remotely sensed images and their applications * Principles and applications of dynamic scene analysis and moving object detection and tracking * Fundamentals of image compression, including the JPEG standard and the new JPEG2000 standard Additional features include problems and solutions with each chapter to help you apply the theory and techniques, as well as bibliographies for researching specialized topics. With its extensive use of examples and illustrative figures, this is a superior title for students and practitioners in computer science, wireless and multimedia communications, and engineering.

Tracking with Particle Filter for High-dimensional Observation and State Spaces

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Publisher : John Wiley & Sons
ISBN 13 : 1119054052
Total Pages : 222 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Tracking with Particle Filter for High-dimensional Observation and State Spaces by : Séverine Dubuisson

Download or read book Tracking with Particle Filter for High-dimensional Observation and State Spaces written by Séverine Dubuisson and published by John Wiley & Sons. This book was released on 2015-01-05 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This title concerns the use of a particle filter framework to track objects defined in high-dimensional state-spaces using high-dimensional observation spaces. Current tracking applications require us to consider complex models for objects (articulated objects, multiple objects, multiple fragments, etc.) as well as multiple kinds of information (multiple cameras, multiple modalities, etc.). This book presents some recent research that considers the main bottleneck of particle filtering frameworks (high dimensional state spaces) for tracking in such difficult conditions.

Computer Vision -- ACCV 2009

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Publisher : Springer Science & Business Media
ISBN 13 : 3642123031
Total Pages : 742 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Computer Vision -- ACCV 2009 by : Hongbin Zha

Download or read book Computer Vision -- ACCV 2009 written by Hongbin Zha and published by Springer Science & Business Media. This book was released on 2010-04-23 with total page 742 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume set LNCS 5994, LNCS 5995, and LNCS 5996 constitutes the thoroughly refereed post-conference proceedings of the 9th Asian Conference on Computer Vision, ACCV 2009, held in Xi'an, China, in September 2009. The 35 revised full papers and 130 revised poster papers of the three volumes were carefully reviewed and seleceted from 670 submissions. The papers are organized in topical sections on multiple view and stereo, face and pose analysis, motion analysis and tracking, segmentation, feature extraction and object detection, image enhancement and visual attention, machine learning algorithms for vision, object categorization and face recognition, biometrics and surveillance, stereo, motion analysis, and tracking, segmentation, detection, color and texture, as well as machine learning, recognition, biometrics and surveillance.

Sequential Monte Carlo Methods in Practice

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Publisher : Springer Science & Business Media
ISBN 13 : 9780387951461
Total Pages : 624 pages
Book Rating : 4.9/5 (514 download)

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Book Synopsis Sequential Monte Carlo Methods in Practice by : Arnaud Doucet

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 2001-06-21 with total page 624 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.

Nonlinear Filters

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Publisher : Ohmsha, Ltd.
ISBN 13 : 4274805026
Total Pages : 457 pages
Book Rating : 4.2/5 (748 download)

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Book Synopsis Nonlinear Filters by : Sueo Sugimoto

Download or read book Nonlinear Filters written by Sueo Sugimoto and published by Ohmsha, Ltd.. This book was released on 2020-12-10 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers a broad range of filter theories, algorithms, and numerical examples. The representative linear and nonlinear filters such as the Kalman filter, the steady-state Kalman filter, the H infinity filter, the extended Kalman filter, the Gaussian sum filter, the statistically linearized Kalman filter, the unscented Kalman filter, the Gaussian filter, the cubature Kalman filter are first visited. Then, the non-Gaussian filters such as the ensemble Kalman filter and the particle filters based on the sequential Bayesian filter and the sequential importance resampling are described, together with their recent advances. Moreover, the information matrix in the nonlinear filtering, the nonlinear smoother based on the Markov Chain Monte Carlo, the continuous-discrete filters, factorized filters, and nonlinear filters based on stochastic approximation method are detailed. 1 Review of the Kalman Filter and Related Filters 2 Information Matrix in Nonlinear Filtering 3 Extended Kalman Filter and Gaussian Sum Filter 4 Statistically Linearized Kalman Filter 5 The Unscented Kalman Filter 6 General Gaussian Filters and Applications 7 The Ensemble Kalman Filter 8 Particle Filter 9 Nonlinear Smoother with Markov Chain Monte Carlo 10 Continuous-Discrete Filters 11 Factorized Filters 12 Nonlinear Filters Based on Stochastic Approximation Method

Particle Filters for Robot Navigation

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Publisher : Now Pub
ISBN 13 : 9781601987587
Total Pages : 86 pages
Book Rating : 4.9/5 (875 download)

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Book Synopsis Particle Filters for Robot Navigation by : Cyrill Stachniss

Download or read book Particle Filters for Robot Navigation written by Cyrill Stachniss and published by Now Pub. This book was released on 2013-12 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: This primer describes particle filters and relevant applications in the context of robot navigation and illustrates that these filters are powerful tools that can robustly estimate the state of the robot and its environment.

Computer Vision and Graphics

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Publisher : Springer Science & Business Media
ISBN 13 : 3642159095
Total Pages : 447 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Computer Vision and Graphics by : Leonard Bolc

Download or read book Computer Vision and Graphics written by Leonard Bolc and published by Springer Science & Business Media. This book was released on 2010-09-09 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: supporting the Conference.