Introduction to Random Signals, Estimation Theory, and Kalman Filtering
Author: M. Sami Fadali
Publisher: Springer Nature
Published:
Total Pages: 489
ISBN-13: 9819980631
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Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises and Solutions
Author: Robert Grover Brown
Publisher: Wiley-Liss
Published: 1997
Total Pages: 504
ISBN-13:
DOWNLOAD EBOOKIn this updated edition the main thrust is on applied Kalman filtering. Chapters 1-3 provide a minimal background in random process theory and the response of linear systems to random inputs. The following chapter is devoted to Wiener filtering and the remainder of the text deals with various facets of Kalman filtering with emphasis on applications. Starred problems at the end of each chapter are computer exercises. The authors believe that programming the equations and analyzing the results of specific examples is the best way to obtain the insight that is essential in engineering work.
Lessons in Estimation Theory for Signal Processing, Communications, and Control
Author: Jerry M. Mendel
Publisher: Pearson Education
Published: 1995-03-14
Total Pages: 891
ISBN-13: 0132440792
DOWNLOAD EBOOKEstimation theory is a product of need and technology. As a result, it is an integral part of many branches of science and engineering. To help readers differentiate among the rich collection of estimation methods and algorithms, this book describes in detail many of the important estimation methods and shows how they are interrelated. Written as a collection of lessons, this book introduces readers o the general field of estimation theory and includes abundant supplementary material.
Kalman Filtering
Author: Mohinder S. Grewal
Publisher: John Wiley & Sons
Published: 2015-02-02
Total Pages: 639
ISBN-13: 111898496X
DOWNLOAD EBOOKThe 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.
Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises and Solutions
Author: Robert Grover Brown
Publisher: Wiley-Liss
Published: 1997
Total Pages: 504
ISBN-13:
DOWNLOAD EBOOKIn this updated edition the main thrust is on applied Kalman filtering. Chapters 1-3 provide a minimal background in random process theory and the response of linear systems to random inputs. The following chapter is devoted to Wiener filtering and the remainder of the text deals with various facets of Kalman filtering with emphasis on applications. Starred problems at the end of each chapter are computer exercises. The authors believe that programming the equations and analyzing the results of specific examples is the best way to obtain the insight that is essential in engineering work.
Fundamentals of High Accuracy Inertial Navigation
Author: Averil Burton Chatfield
Publisher: AIAA
Published: 1997
Total Pages: 368
ISBN-13: 9781600864278
DOWNLOAD EBOOKEstimation with Applications to Tracking and Navigation
Author: Yaakov Bar-Shalom
Publisher: John Wiley & Sons
Published: 2004-04-05
Total Pages: 583
ISBN-13: 0471465216
DOWNLOAD EBOOKExpert 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.
Random Signal Processing
Author: Dwight F. Mix
Publisher: Macmillan College
Published: 1995
Total Pages: 472
ISBN-13:
DOWNLOAD EBOOKProviding detailed coverage of Wiener filtering and Kalman filtering, this book presents a coherent treatment of estimation theory and an in-depth look at detection theory for communication and pattern recognition.
RANDOM PROCESSES: FILTERING, ESTIMATION AND DETECTION
Author: Lonnie C. Ludeman
Publisher:
Published: 2010-07-01
Total Pages: 628
ISBN-13: 9788126527236
DOWNLOAD EBOOKMarket_Desc: Graduate students of electrical and computer engineering. Practicing engineers in communications and signal processing. Special Features: " Covers modern detection and estimation theory as well as the basics of random processes" Emphasizes the use of discrete-time Weiner and Kalman filters and covers nonlinear systems in detail" Includes over 380 class-tested homework exercises About The Book: An understanding of random processes is crucial in the study of many engineering systems, for example analyzing noise in a wireless communications channel. This book covers the basics of probability and random processes for an engineering audience. Importantly, though, the book also presents the details of modern detection and estimation theory, giving it a real edge over existing textbooks. The author has a proven track record. His book Fundamentals of Digital Signal Processing has sold 15,000 copies and won Choice magazine's Outstanding Engineering Book of the Year award.
Probability, Random Variables, and Random Processes
Author: John J. Shynk
Publisher: John Wiley & Sons
Published: 2012-10-15
Total Pages: 850
ISBN-13: 1118393953
DOWNLOAD EBOOKProbability, Random Variables, and Random Processes is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses. It is intended for first-year graduate students who have some familiarity with probability and random variables, though not necessarily of random processes and systems that operate on random signals. It is also appropriate for advanced undergraduate students who have a strong mathematical background. The book has the following features: Several appendices include related material on integration, important inequalities and identities, frequency-domain transforms, and linear algebra. These topics have been included so that the book is relatively self-contained. One appendix contains an extensive summary of 33 random variables and their properties such as moments, characteristic functions, and entropy. Unlike most books on probability, numerous figures have been included to clarify and expand upon important points. Over 600 illustrations and MATLAB plots have been designed to reinforce the material and illustrate the various characterizations and properties of random quantities. Sufficient statistics are covered in detail, as is their connection to parameter estimation techniques. These include classical Bayesian estimation and several optimality criteria: mean-square error, mean-absolute error, maximum likelihood, method of moments, and least squares. The last four chapters provide an introduction to several topics usually studied in subsequent engineering courses: communication systems and information theory; optimal filtering (Wiener and Kalman); adaptive filtering (FIR and IIR); and antenna beamforming, channel equalization, and direction finding. This material is available electronically at the companion website. Probability, Random Variables, and Random Processes is the only textbook on probability for engineers that includes relevant background material, provides extensive summaries of key results, and extends various statistical techniques to a range of applications in signal processing.
