Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises and Solutions
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:

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In 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.

Random Signal Processing
Random Signal Processing

Author: Dwight F. Mix

Publisher: Macmillan College

Published: 1995

Total Pages: 472

ISBN-13:

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Providing 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.

Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation

Author: Yaakov Bar-Shalom

Publisher: John Wiley & Sons

Published: 2004-04-05

Total Pages: 583

ISBN-13: 0471465216

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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.

Kalman Filtering
Kalman Filtering

Author: Mohinder S. Grewal

Publisher: John Wiley & Sons

Published: 2015-02-02

Total Pages: 639

ISBN-13: 111898496X

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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.

Optimal Filtering
Optimal Filtering

Author: Brian D. O. Anderson

Publisher: Courier Corporation

Published: 2012-05-23

Total Pages: 370

ISBN-13: 0486136892

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Graduate-level text extends studies of signal processing, particularly regarding communication systems and digital filtering theory. Topics include filtering, linear systems, and estimation; discrete-time Kalman filter; time-invariant filters; more. 1979 edition.

Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises
Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises

Author: Robert Grover Brown

Publisher: John Wiley & Sons

Published: 2012-02-07

Total Pages: 0

ISBN-13: 9780470609699

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Advances in computers and personal navigation systems have greatly expanded the applications of Kalman filters. A Kalman filter uses information about noise and system dynamics to reduce uncertainty from noisy measurements. Common applications of Kalman filters include such fast-growing fields as autopilot systems, battery state of charge (SoC) estimation, brain-computer interface, dynamic positioning, inertial guidance systems, radar tracking, and satellite navigation systems. Brown and Hwang's bestselling textbook introduces the theory and applications of Kalman filters for senior undergraduates and graduate students. This revision updates both the research advances in variations on the Kalman filter algorithm and adds a wide range of new application examples. The book emphasizes the application of computational software tools such as MATLAB. The companion website includes M-files to assist students in applying MATLAB to solving end-of-chapter homework problems.

An Introduction to Statistical Signal Processing
An Introduction to Statistical Signal Processing

Author: Robert M. Gray

Publisher: Cambridge University Press

Published: 2004-12-02

Total Pages: 479

ISBN-13: 1139456288

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This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing using a range of carefully chosen examples. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book. Hundreds of homework problems are included and the book is ideal for graduate students of electrical engineering and applied mathematics. It is also a useful reference for researchers in signal processing and communications.