Search Results: estimation-with-applications-to-tracking-and-navigation

Estimation with Applications to Tracking and Navigation

Theory Algorithms and Software

Author: Yaakov Bar-Shalom,X. Rong Li,Thiagalingam Kirubarajan

Publisher: John Wiley & Sons

ISBN: 0471465216

Category: Technology & Engineering

Page: 584

View: 1036

Expert coverage of the design and implementation of state estimation algorithms for tracking and navigation Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a balanced combination of linear systems, probability, and statistics. The authors provide a review of the necessary background mathematical techniques and offer an overview of the basic concepts in estimation. They then provide detailed treatments of all the major issues in estimation with a focus on applying these techniques to real systems. Other features include: Problems that apply theoretical material to real-world applications In-depth coverage of the Interacting Multiple Model (IMM) estimator Companion DynaEst(TM) software for MATLAB(TM) implementation of Kalman filters and IMM estimators Design guidelines for tracking filters Suitable for graduate engineering students and engineers working in remote sensors and tracking, Estimation with Applications to Tracking and Navigation provides expert coverage of this important area.

Multitarget-multisensor Tracking

Applications and Advances

Author: Yaakov Bar-Shalom

Publisher: Artech House on Demand

ISBN: 9780890065174

Category: Technology & Engineering

Page: 442

View: 4758

Compiles the latest techniques for those who design advanced systems for tracking, surveillance and navigation. This second volume expands upon the first with 11 new chapters. The text includes pertinent contributions from leading international experts in this field.

Fundamentals of Object Tracking

Author: Sudha Challa

Publisher: Cambridge University Press

ISBN: 0521876281

Category: Mathematics

Page: 375

View: 355

Introduces object tracking algorithms from a unified, recursive Bayesian perspective, along with performance bounds and illustrative examples.

Advanced Kalman Filtering, Least-Squares and Modeling

A Practical Handbook

Author: Bruce P. Gibbs

Publisher: John Wiley & Sons

ISBN: 1118003160

Category: Technology & Engineering

Page: 640

View: 1242

This book is intended primarily as a handbook for engineers who must design practical systems. Its primary goal is to discuss model development in sufficient detail so that the reader may design an estimator that meets all application requirements and is robust to modeling assumptions. Since it is sometimes difficult to a priori determine the best model structure, use of exploratory data analysis to define model structure is discussed. Methods for deciding on the “best” model are also presented. A second goal is to present little known extensions of least squares estimation or Kalman filtering that provide guidance on model structure and parameters, or make the estimator more robust to changes in real-world behavior. A third goal is discussion of implementation issues that make the estimator more accurate or efficient, or that make it flexible so that model alternatives can be easily compared. The fourth goal is to provide the designer/analyst with guidance in evaluating estimator performance and in determining/correcting problems. The final goal is to provide a subroutine library that simplifies implementation, and flexible general purpose high-level drivers that allow both easy analysis of alternative models and access to extensions of the basic filtering. Supplemental materials and up-to-date errata are downloadable at

Tracking and Data Association

Author: Yaakov Bar-Shalom,Thomas E. Fortmann

Publisher: Elsevier Science Limited


Category: Mathematics

Page: 353

View: 9309

In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation; methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; and methods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory. As a result, the book represents a blend of new methods in general computational analysis, and specific, but also generic, techniques for study of systems theory ant its particular branches, such as optimal filtering and information compression. - Best operator approximation, - Non-Lagrange interpolation, - Generic Karhunen-Loeve transform - Generalised low-rank matrix approximation - Optimal data compression - Optimal nonlinear filtering

Optimal Estimation of Dynamic Systems

Author: John L. Crassidis,John L. Junkins

Publisher: CRC Press

ISBN: 1135439273

Category: Mathematics

Page: 608

View: 7134

Most newcomers to the field of linear stochastic estimation go through a difficult process in understanding and applying the theory.This book minimizes the process while introducing the fundamentals of optimal estimation. Optimal Estimation of Dynamic Systems explores topics that are important in the field of control where the signals received are used to determine highly sensitive processes such as the flight path of a plane, the orbit of a space vehicle, or the control of a machine. The authors use dynamic models from mechanical and aerospace engineering to provide immediate results of estimation concepts with a minimal reliance on mathematical skills. The book documents the development of the central concepts and methods of optimal estimation theory in a manner accessible to engineering students, applied mathematicians, and practicing engineers. It includes rigorous theoretial derivations and a significant amount of qualitiative discussion and judgements. It also presents prototype algorithms, giving detail and discussion to stimulate development of efficient computer programs and intelligent use of them. This book illustrates the application of optimal estimation methods to problems with varying degrees of analytical and numercial difficulty. It compares various approaches to help develop a feel for the absolute and relative utility of different methods, and provides many applications in the fields of aerospace, mechanical, and electrical engineering.

Tracking and Kalman filtering made easy

Author: Eli Brookner

Publisher: Wiley-Interscience

ISBN: 9780471184072

Category: Technology & Engineering

Page: 477

View: 7334

A unique, easy-to-use guide to radar tracking and Kalman filtering This book presents the first truly accessible treatment of radar tracking; Kalman, Swerling, and Bayes filters for linear and nonlinear ballistic and satellite tracking systems; and the voltage-processing methods (Givens, Householder, and Gram-Schmidt) for least-squares filtering to correct for computer round-off errors. Tracking and Kalman Filtering Made Easy emphasizes the physical and geometric aspects of radar filters as well as the beauty and simplicity of their mathematics. An abundance of design equations, procedures, and curves allows readers to design tracking filters quickly and test their performance using only a pocket calculator! The text incorporates problems and solutions, figures and photographs, and astonishingly simple derivations for various filters. It tackles problems involving clutter returns, redundant target detections, inconsistent data, track-start and track-drop rules, data association, matched filtering, tracking with chirp waveform, and more. The book also covers useful techniques such as the moving target detector (MTD) clutter rejection technique. All explanations are given in clear and simple terms, including: * The voltage-processing approach to least-squares filtering * The correlation between such procedures as discrete orthogonal Legendre polynomial (DOLP) and voltage processing * The mathematical sameness of tracking and estimation problems on the one hand, and sidelobe canceling and adaptive array processing on the other * The massively parallel systolic array sidelobe canceler processor * Important computational accuracy issues * An appended comparison between the Kalman and the Swerling filters, written by Dr. Peter Swerling Tracking and Kalman Filtering Made Easy is invaluable for engineers, scientists, and mathematicians involved in tracking filter design. Its straightforward approach makes it an excellent textbook for senior-undergraduate and first-year graduate courses.

Bayesian Estimation and Tracking

A Practical Guide

Author: Anton J. Haug

Publisher: John Wiley & Sons

ISBN: 1118287800

Category: Mathematics

Page: 448

View: 335

A practical approach to estimating and tracking dynamic systems in real-worl applications Much of the literature on performing estimation for non-Gaussian systems is short on practical methodology, while Gaussian methods often lack a cohesive derivation. Bayesian Estimation and Tracking addresses the gap in the field on both accounts, providing readers with a comprehensive overview of methods for estimating both linear and nonlinear dynamic systems driven by Gaussian and non-Gaussian noices. Featuring a unified approach to Bayesian estimation and tracking, the book emphasizes the derivation of all tracking algorithms within a Bayesian framework and describes effective numerical methods for evaluating density-weighted integrals, including linear and nonlinear Kalman filters for Gaussian-weighted integrals and particle filters for non-Gaussian cases. The author first emphasizes detailed derivations from first principles of eeach estimation method and goes on to use illustrative and detailed step-by-step instructions for each method that makes coding of the tracking filter simple and easy to understand. Case studies are employed to showcase applications of the discussed topics. In addition, the book supplies block diagrams for each algorithm, allowing readers to develop their own MATLAB® toolbox of estimation methods. Bayesian Estimation and Tracking is an excellent book for courses on estimation and tracking methods at the graduate level. The book also serves as a valuable reference for research scientists, mathematicians, and engineers seeking a deeper understanding of the topics.

Kalman Filtering and Neural Networks

Author: Simon Haykin

Publisher: John Wiley & Sons

ISBN: 047146421X

Category: Technology & Engineering

Page: 284

View: 2951

State-of-the-art coverage of Kalman filter methods for the design of neural networks This self-contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks. Although the traditional approach to the subject is almost always linear, this book recognizes and deals with the fact that real problems are most often nonlinear. The first chapter offers an introductory treatment of Kalman filters with an emphasis on basic Kalman filter theory, Rauch-Tung-Striebel smoother, and the extended Kalman filter. Other chapters cover: An algorithm for the training of feedforward and recurrent multilayered perceptrons, based on the decoupled extended Kalman filter (DEKF) Applications of the DEKF learning algorithm to the study of image sequences and the dynamic reconstruction of chaotic processes The dual estimation problem Stochastic nonlinear dynamics: the expectation-maximization (EM) algorithm and the extended Kalman smoothing (EKS) algorithm The unscented Kalman filter Each chapter, with the exception of the introduction, includes illustrative applications of the learning algorithms described here, some of which involve the use of simulated and real-life data. Kalman Filtering and Neural Networks serves as an expert resource for researchers in neural networks and nonlinear dynamical systems. An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley Makerting Department.

Multiple-target Tracking with Radar Applications

Author: Samuel S. Blackman

Publisher: Artech House on Demand


Category: Technology & Engineering

Page: 449

View: 4844

Kalman Filtering

Theory and Practice with MATLAB

Author: Mohinder S. Grewal,Angus P. Andrews

Publisher: John Wiley & Sons

ISBN: 111898496X

Category: Technology & Engineering

Page: 640

View: 4220

The definitive textbook and professional reference on Kalman Filtering – fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.

Integrated Aircraft Navigation

Author: James Farrell

Publisher: Elsevier

ISBN: 0323153798

Category: Transportation

Page: 368

View: 482

Integrated Aircraft Navigation discusses the fundamentals of navigation systems analysis. Modern aircraft navigation systems are characterized by a multifaceted, computer-oriented approach, covering various branches of theoretical dynamics, inertial measurements, radar, radio navaids, celestial observations, and widely used statistical estimation techniques. Each pertinent field entails much technological development that is not essential for applied systems analysis. The book presents pertinent information extracted from a broad range of topics, expressed in terms of Newtonian physics and matrix-vector mathematics. The book begins by defining basic navigation quantities and functions, and introducing various subjects as an aid to subsequent developments. These include basic motion patterns, navigation coordinate frames, and navigation techniques and requirements. This is followed by separate chapters on coordinate transformations and kinematics; inertial navigation theory; the physics of inertial measurements; and navigation with multiple sensors. Subsequent chapters deal with dynamic equations for all navigation modes considered; functional relationships and practical considerations for the various navigation aid sensors in common usage; and system applications. This book will be useful to the student or practicing engineer who wants a valid analytical characterization, using the simplest theoretical concepts permissible, while omitting specialized mechanization details.

Design and Analysis of Modern Tracking Systems

Author: Samuel S. Blackman,Robert Popoli

Publisher: Artech House Publishers

ISBN: 9781580530064

Category: Technology & Engineering

Page: 1230

View: 976

An overview of the state in design and implementation of advanced tracking for single and multiple sensor systems. The text provides evaluations of sensor management, kinematic and attribute data processing, data association, situation assessment, and modern tracking and data fusion methods as applied in both military and non-military arenas.

Applied State Estimation and Association

Author: Chaw-Bing Chang,Keh-Ping Dunn

Publisher: MIT Press

ISBN: 026203400X

Category: Technology & Engineering

Page: 472

View: 8626

A rigorous introduction to the theory and applications of state estimation and association, an important area in aerospace, electronics, and defense industries.

Kalman Filtering

Theory and Application

Author: Harold Wayne Sorenson

Publisher: IEEE


Category: Kalman filtering

Page: 457

View: 8772

Understanding Satellite Navigation

Author: Rajat Acharya

Publisher: Academic Press

ISBN: 0128001895

Category: Technology & Engineering

Page: 384

View: 5360

This book explains the basic principles of satellite navigation technology with the bare minimum of mathematics and without complex equations. It helps you to conceptualize the underlying theory from first principles, building up your knowledge gradually using practical demonstrations and worked examples. A full range of MATLAB simulations is used to visualize concepts and solve problems, allowing you to see what happens to signals and systems with different configurations. Implementation and applications are discussed, along with some special topics such as Kalman Filter and Ionosphere. With this book you will learn: How a satellite navigation system works How to improve your efficiency when working with a satellite navigation system How to use MATLAB for simulation, helping to visualize concepts Various possible implementation approaches for the technologyThe most significant applications of satellite navigation systems Teaches the fundamentals of satellite navigation systems, using MATLAB as a visualization and problem solving tool Worked out numerical problems are provided to aid practical understanding On-line support provides MATLAB scripts for simulation exercises and MATLAB based solutions, standard algorithms, and PowerPoint slides

Multisensor Attitude Estimation

Fundamental Concepts and Applications

Author: Hassen Fourati,Djamel Eddine Chouaib Belkhiat

Publisher: CRC Press

ISBN: 1498745806

Category: Technology & Engineering

Page: 580

View: 9909

There has been an increasing interest in multi-disciplinary research on multisensor attitude estimation technology driven by its versatility and diverse areas of application, such as sensor networks, robotics, navigation, video, biomedicine, etc. Attitude estimation consists of the determination of rigid bodies’ orientation in 3D space. This research area is a multilevel, multifaceted process handling the automatic association, correlation, estimation, and combination of data and information from several sources. Data fusion for attitude estimation is motivated by several issues and problems, such as data imperfection, data multi-modality, data dimensionality, processing framework, etc. While many of these problems have been identified and heavily investigated, no single data fusion algorithm is capable of addressing all the aforementioned challenges. The variety of methods in the literature focus on a subset of these issues to solve, which would be determined based on the application in hand. Historically, the problem of attitude estimation has been introduced by Grace Wahba in 1965 within the estimate of satellite attitude and aerospace applications. This book intends to provide the reader with both a generic and comprehensive view of contemporary data fusion methodologies for attitude estimation, as well as the most recent researches and novel advances on multisensor attitude estimation task. It explores the design of algorithms and architectures, benefits, and challenging aspects, as well as a broad array of disciplines, including: navigation, robotics, biomedicine, motion analysis, etc. A number of issues that make data fusion for attitude estimation a challenging task, and which will be discussed through the different chapters of the book, are related to: 1) The nature of sensors and information sources (accelerometer, gyroscope, magnetometer, GPS, inclinometer, etc.); 2) The computational ability at the sensors; 3) The theoretical developments and convergence proofs; 4) The system architecture, computational resources, fusion level.

Advances in Estimation, Navigation, and Spacecraft Control

Selected Papers of the Itzhack Y. Bar-Itzhack Memorial Symposium on Estimation, Navigation, and Spacecraft Control

Author: Daniel Choukroun,Yaakov Oshman,Julie Thienel,Moshe Idan

Publisher: Springer

ISBN: 3662447851

Category: Technology & Engineering

Page: 550

View: 3185

This book presents selected papers of the Itzhack Y. Bar-Itzhack Memorial Sympo- sium on Estimation, Navigation, and Spacecraft Control. Itzhack Y. Bar-Itzhack, professor Emeritus of Aerospace Engineering at the Technion – Israel Institute of Technology, was a prominent and world-renowned member of the applied estimation, navigation, and spacecraft attitude determination communities. He touched the lives of many. He had a love for life, an incredible sense of humor, and wisdom that he shared freely with everyone he met. To honor Professor Bar-Itzhack's memory, as well as his numerous seminal professional achievements, an international symposium was held in Haifa, Israel, on October 14–17, 2012, under the auspices of the Faculty of Aerospace Engineering at the Technion and the Israeli Association for Automatic Control. The book contains 27 selected, revised, and edited contributed chapters written by eminent international experts. The book is organized in three parts: (1) Estimation, (2) Navigation and (3) Spacecraft Guidance, Navigation and Control. The volume was prepared as a reference for research scientists and practicing engineers from academy and industry in the fields of estimation, navigation, and spacecraft GN&C.

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