estimation with applications to tracking and navigation theory algorithms and software

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Estimation With Applications To Tracking And Navigation

Author : Yaakov Bar-Shalom
ISBN : 9780471465218
Genre : Technology & Engineering
File Size : 42. 8 MB
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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.

Tracking And Data Association

Author : Yaakov Bar-Shalom
ISBN : UOM:39015013064426
Genre : Mathematics
File Size : 75. 66 MB
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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

Advanced Kalman Filtering Least Squares And Modeling

Author : Bruce P. Gibbs
ISBN : 9781118003169
Genre : Technology & Engineering
File Size : 29. 88 MB
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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

Multiple Target Tracking With Radar Applications

Author : Samuel S. Blackman
ISBN : UOM:39015010635632
Genre : Technology & Engineering
File Size : 88. 43 MB
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Applied State Estimation And Association

Author : Chaw-Bing Chang
ISBN : 9780262034005
Genre : Technology & Engineering
File Size : 47. 90 MB
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A rigorous introduction to the theory and applications of state estimation and association, an important area in aerospace, electronics, and defense industries.

Tracking And Data Fusion

Author : Yaakov Bar-Shalom
ISBN : 0964831279
Genre : Algorithms
File Size : 75. 16 MB
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Tracking And Kalman Filtering Made Easy

Author : Eli Brookner
ISBN : 0471184071
Genre : Technology & Engineering
File Size : 60. 71 MB
Format : PDF, ePub
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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.

Fundamentals Of Object Tracking

Author : Sudha Challa
ISBN : 9780521876285
Genre : Mathematics
File Size : 69. 13 MB
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Introduces object tracking algorithms from a unified, recursive Bayesian perspective, along with performance bounds and illustrative examples.

Statistical Orbit Determination

Author : Bob Schutz
ISBN : 9780080541730
Genre : Science
File Size : 46. 15 MB
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Statistical Orbit Determination presents fundmentals of orbit determination--from weighted least squares approaches (Gauss) to today's high-speed computer algorithms that provide accuracy within a few centimeters. Numerous examples and problems are provided to enhance readers' understanding of the material. Covers such topics as coordinate and time systems, square root filters, process noise techniques, and the use of fictitious parameters for absorbing un-modeled and incorrectly modeled forces acting on a satellite. Examples and exercises serve to illustrate the principles throughout each chapter.

Kalman Filtering And Neural Networks

Author : Simon Haykin
ISBN : 9780471464211
Genre : Technology & Engineering
File Size : 81. 82 MB
Format : PDF, Kindle
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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.

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