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Author: S. M. Bozic Publisher: Courier Dover Publications ISBN: 0486817350 Category : Technology & Engineering Languages : en Pages : 179
Book Description
The first half of this concise introductory treatment focuses on digital filtering and the second on filtering noisy data to extract a signal. The text includes worked examples and problems with solutions. 1994 edition.
Author: S. M. Bozic Publisher: Courier Dover Publications ISBN: 0486817350 Category : Technology & Engineering Languages : en Pages : 179
Book Description
The first half of this concise introductory treatment focuses on digital filtering and the second on filtering noisy data to extract a signal. The text includes worked examples and problems with solutions. 1994 edition.
Author: Svetozar Mile Bozic Publisher: Edward Arnold ISBN: 9780713134100 Category : Digital filters (Mathematics) Languages : en Pages : 157
Book Description
This text provides a concise introduction to digital filtering, filter design and applications in the form of the Kalman and Wiener filters. Throughout the book, concepts are developed gradually and the material is presented systematically with appropriate illustrations.
Author: Charles K. Chui Publisher: Springer Science & Business Media ISBN: 366202666X Category : Science Languages : en Pages : 209
Book Description
In addition to making a number of minor corrections and updat ing the references, we have expanded the section on "real-time system identification" in Chapter 10 of the first edition into two sections and combined it with Chapter 8. In its place, a very brief introduction to wavelet analysis is included in Chapter 10. Although the pyramid algorithms for wavelet decompositions and reconstructions are quite different from the Kalman filtering al gorithms, they can also be applied to time-domain filtering, and it is hoped that splines and wavelets can be incorporated with Kalman filtering in the near future. College Station and Houston Charles K. Chui September 1990 Guanrong Chen Preface to the First Edition Kalman filtering is an optimal state estimation process applied to a dynamic system that involves random perturbations. More precisely, the Kalman filter gives a linear, unbiased, and min imum error variance recursive algorithm to optimally estimate the unknown state of a dynamic system from noisy data taken at discrete real-time. It has been widely used in many areas of industrial and government applications such as video and laser tracking systems, satellite navigation, ballistic missile trajectory estimation, radar, and fire control. With the recent development of high-speed computers, the Kalman filter has become more use ful even for very complicated real-time applications.
Author: S. M. Bozic Publisher: Wiley ISBN: 9780470269244 Category : Technology & Engineering Languages : en Pages : 157
Book Description
Provides a basic introduction to digital filtering, filter design, and application in the form of Kalman and Wiener filters. The approach used throughout the book is a transition from continuous-to-discrete-time systems, since electrical engineering is usually taught from continuous-time concepts. Various central topics are developed gradually with a number of examples and problems with solutions. The book is suitable both as an undergraduate and as a postgraduate text.
Author: Mohinder S. Grewal Publisher: John Wiley & Sons ISBN: 111898496X Category : Technology & Engineering Languages : en Pages : 639
Book Description
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.
Author: Paul Zarchan Publisher: AIAA (American Institute of Aeronautics & Astronautics) ISBN: 9781600867187 Category : Aeronautics Languages : en Pages : 0
Book Description
Numerical basics -- Method of least squares -- Recursive least-squares filtering -- Polynomial Kalman filters -- Kalman filters in a nonpolynomial world -- Continuous polynomial Kalman filter -- Extended Kalman filtering -- Drag and falling object -- Cannon-launched projectile tracking problem -- Tracking a sine wave -- Satellite navigation -- Biases -- Linearized Kalman filtering -- Miscellaneous topics -- Fading-memory filter -- Assorted techniques for improving Kalman-filter performance -- Fixed-memory filters -- Chain-rule and least-squares filtering -- Filter bank approach to tracking a sine wave -- Appendix A: Fundamentals of Kalman-filtering software -- Appendix B: Key formula and concept summary
Author: Narayan Kovvali Publisher: Morgan & Claypool Publishers ISBN: 1627051406 Category : Technology & Engineering Languages : en Pages : 83
Book Description
The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a variety of applications, e.g., target tracking, guidance and navigation, and communications systems. The purpose of this book is to present a brief introduction to Kalman filtering. The theoretical framework of the Kalman filter is first presented, followed by examples showing its use in practical applications. Extensions of the method to nonlinear problems and distributed applications are discussed. A software implementation of the algorithm in the MATLAB programming language is provided, as well as MATLAB code for several example applications discussed in the manuscript.
Author: K.V. Ramachandra Publisher: CRC Press ISBN: 9780824793227 Category : Technology & Engineering Languages : en Pages : 258
Book Description
A review of effective radar tracking filter methods and their associated digital filtering algorithms. It examines newly developed systems for eliminating the real-time execution of complete recursive Kalman filtering matrix equations that reduce tracking and update time. It also focuses on the role of tracking filters in operations of radar data processors for satellites, missiles, aircraft, ships, submarines and RPVs.
Author: Armando Barreto Publisher: CRC Press ISBN: 0429577567 Category : Computers Languages : en Pages : 248
Book Description
The emergence of affordable micro sensors, such as MEMS Inertial Measurement Systems, which are being applied in embedded systems and Internet-of-Things devices, has brought techniques such as Kalman Filtering, capable of combining information from multiple sensors or sources, to the interest of students and hobbyists. This will book will develop just the necessary background concepts, helping a much wider audience of readers develop an understanding and intuition that will enable them to follow the explanation for the Kalman Filtering algorithm
Author: Hongbin Ma Publisher: Springer Nature ISBN: 9811508062 Category : Technology & Engineering Languages : en Pages : 295
Book Description
This book addresses a key technology for digital information processing: Kalman filtering, which is generally considered to be one of the greatest discoveries of the 20th century. It introduces readers to issues concerning various uncertainties in a single plant, and to corresponding solutions based on adaptive estimation. Further, it discusses in detail the issues that arise when Kalman filtering technology is applied in multi-sensor systems and/or multi-agent systems, especially when various sensors are used in systems like intelligent robots, autonomous cars, smart homes, smart buildings, etc., requiring multi-sensor information fusion techniques. Furthermore, when multiple agents (subsystems) interact with one another, it produces coupling uncertainties, a challenging issue that is addressed here with the aid of novel decentralized adaptive filtering techniques.Overall, the book’s goal is to provide readers with a comprehensive investigation into the challenging problem of making Kalman filtering work well in the presence of various uncertainties and/or for multiple sensors/components. State-of-art techniques are introduced, together with a wealth of novel findings. As such, it can be a good reference book for researchers whose work involves filtering and applications; yet it can also serve as a postgraduate textbook for students in mathematics, engineering, automation, and related fields.To read this book, only a basic grasp of linear algebra and probability theory is needed, though experience with least squares, navigation, robotics, etc. would definitely be a plus.
Author: S. M. Bozic
Author: S. M. Bozic
Author: Svetozar Mile Bozic
Author: Charles K. Chui
Author: S. M. Bozic
Author: Mohinder S. Grewal
Author: Paul Zarchan
Author: Narayan Kovvali
Author: K.V. Ramachandra
Author: Armando Barreto
Author: Hongbin Ma