Book Description
". . . an authentic magnum opus worth much more than its weight in gold!"-IEEE Transactions on Automatic Control, from a review of the First Edition
"The best book I've seen on the subject of Kalman filtering . . . Reading other books on Kalman filters and not this one could make you a very dangerous Kalman filter engineer."-Amazon.com, from a review of the First Edition
In this practical introduction to Kalman filtering theory and applications, authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common problems, and limitations of estimation theory as it applies to real-world situations. They provide many illustrative examples drawn from an array of application areas including GPS-aided INS, the modeling of gyros and accelerometers, inertial navigation, and freeway traffic control. In addition, they share many hard-won lessons about, and original methods for, designing, implementing, validating, and improving Kalman filters, including techniques for:
* Representing the problem in a mathematical model
* Analyzing estimator performance as a function of model parameters
* Implementing the mechanization equations in numerically stable algorithms
* Assessing computational requirements
* Testing the validity of results
* Monitoring filter performance in operation
As the best way to understand and master a technology is to observe it in action, Kalman Filtering: Theory and Practice Using MATLAB(r), Second Edition includes companion software in MATLAB(r), providing users with an opportunity to experience first hand the filter's workings and its limitations.
This updated and revised edition of Grewal and Andrews's classic guide is an indispensable working resource for engineers and computer scientists involved in the design of aerospace and aeronautical systems, global positioning and radar tracking systems, power systems, and biomedical instrumentation.
An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Customer Reviews:
Not enough examples..........2004-03-19
This book is difficult to understand due to the lack of simple examples to illustrate keep points as they are introduced.
There are a few examples in each chapter, however the authors skip too many steps and make you constantly flip around in the book to review previous examples upon which he bases the new examples. The end result is just wasteful trashing by the student.
This is a good book, but it does't have enough textbook examples to be used for an intro class in Kalam filtering.
Maybe this book would be useful as a secondary reference for a person that already knows Kalman filtering.
Most useful text on the subject.......2002-12-03
I have been working with "Kalman Fitering, ... Using Matlab",
2nd Edition, for several weeks, and I must tell you it is by far the
most useful text on the subject.
Kalman what???.......2002-11-27
I have to say this is a strange book on Kalman filtering - the structure of the book is probably as incoherent as the presentation. It is not a good book for a student wishing to learn Kalman Filtering and how to adapt it to practical problems.
I think the authors assume that the readers all know about Kalman filters and as far as introductions are concerned, only need to know the history of it. Indeed it is not until chapter 4.2 that you get any acknowledgement of the actual filter the rest of the book is peripheral information that would apply if you were a seasoned Kalman Filter expert.
The weird thing is that anyone with a detailed knowledge of Kalman Filtering would certainly know everything there was to know about matrix algebra, and so Appendix B has a tutorial or refresher on matrix forms - weird.
The notation also appears non standard and there are many sections where equation variables are not well explained and the examples very obsure and the premable non existent.
This is not a good book for any one wishing to either familiarise themselves with Kalman filtering - there is some good information in this but it is not a text book by any stretch of the imagination.
Book Description
An updated guide to GNSS and INS, and solutions to real-world GPS/INS problems with Kalman filtering
Written by recognized authorities in the field, this second edition of a landmark work provides engineers, computer scientists, and others with a working familiarity with the theory and contemporary applications of Global Navigation Satellite Systems (GNSS), Inertial Navigational Systems (INS), and Kalman filters. Throughout, the focus is on solving real-world problems, with an emphasis on the effective use of state-of-the-art integration techniques for those systems, especially the application of Kalman filtering. To that end, the authors explore the various subtleties, common failures, and inherent limitations of the theory as it applies to real-world situations, and provide numerous detailed application examples and practice problems, including GNSS-aided INS, modeling of gyros and accelerometers, and SBAS and GBAS.
Drawing upon their many years of experience with GNSS, INS, and the Kalman filter, the authors present numerous design and implementation techniques not found in other professional references. This Second Edition has been updated to include:
- GNSS signal integrity with SBAS
- Mitigation of multipath, including results
- Ionospheric delay estimation with Kalman filters
- New MATLAB programs for satellite position determination using almanac and ephemeris data and ionospheric delay calculations from single and dual frequency data
- New algorithms for GEO with L1 /L5 frequencies and clock steering
- Implementation of mechanization equations in numerically stable algorithms
To enhance comprehension of the subjects covered, the authors have included software in MATLAB, demonstrating the working of the GNSS, INS, and filter algorithms. In addition to showing the Kalman filter in action, the software also demonstrates various practical aspects of finite word length arithmetic and the need for alternative algorithms to preserve result accuracy.
Download Description
The only comprehensive guide to Kalman filtering and its applications to real-world GPS/INS problems Written by recognized authorities in the field, this book provides engineers, computer scientists, and others with a working familiarity with the theory and contemporary applications of Global Positioning Systems (GPS), Inertial Navigational Systems, and Kalman filters. Throughout, the focus is on solving real-world problems, with an emphasis on the effective use of state-of-the-art integration techniques for those systems, especially the application of Kalman filtering. To that end, the authors explore the various subtleties, common failures, and inherent limitations of the theory as it applies to real-world situations, and provide numerous detailed application examples and practice problems, including GPS-aided INS, modeling of gyros and accelerometers, and WAAS and LAAS. Drawing upon their many years of experience with GPS, INS, and the Kalman filter, the authors present numerous design and implementation techniques not found in other professional references, including original techniques for: * Representing the problem in a mathematical model * Analyzing the performance of the GPS sensor as a function of model parameters * Implementing the mechanization equations in numerically stable algorithms * Assessing computation requirements * Testing the validity of results * Monitoring GPS, INS, and Kalman filter performance in operation In order to enhance comprehension of the subjects covered, the authors have included software in MATLAB, demonstrating the workings of the GPS, INS, and filter algorithms. In addition to showing the Kalman filter in action, the software also demonstrates various practical aspects of finite word length arithmetic and the need for alternative algorithms to preserve result accuracy.
Customer Reviews:
Excellent source for basic understanding of Kalman Filtering.......2005-12-28
This book constitutes an excellent source for understanding the basic operation of the Global Positioning Systems (GPS). It also allows the reader to take the first steps towards understanding how the Kalman Filter is implemented in the estimation of drifting parameters of the GPS. The "Kalman Filter Basics" chapter is preceded by a description of the different errors that affect the GPS signals. Furthermore, this book includes sections on the Wide-Area Augmentation System, Inertial Navigation, and Differential GPS, which enables the understanding of these concepts and thus, provides the reader an overall perspective of the Global Positioning System.
The book also includes a detailed explanation of the characteristics of the GPS signal, as well as the design of the receiver and antennas.
Finally, details on the mathematical operations included throughout the chapters, are explained in three (3) Appendixes. Overall, this is a great book for understanding the overall performance of the Global Positioning System, and the relevant aspects which it entails.
Best source of information on GPS.......2002-12-03
One of the students in my lecture came up to me and said he had studied this book all summer to learn about GPS. He found it to be very helpful to him and he said it was the best source of information on GPS he had come across.
GPS World Magazine reviewer recommends this book.......2001-10-12
Here are some quotes from a review of this book in GPS World, July 2001, pp 46-47, by Dr. John Angus, a consultant and researcher in the area of GPS-aided navigation systems, AND professor at Claremont Graduate University, Claremont, CA. Dr. Angus' credentials qualify him to review this book.
"Noteworthy is the comprehensiveness of the material on GPS, Kalman filtering and Kalman filter engineering, and the appendix on coordinate transforms...An instructor could easily develop a one-semester course on basic GPS or a full year course on GPS and inertial navigation, each of them "glued" together by the Kalman filter and enlivened by computer experiments with the MATLAB code provided."
"The writing...tends to be concise and the mathematics is kept to the minimum necessary to expose the theory and methods of filtering, GPS, and INS."
"...effectively addresses most of the basic engineering and performance issues relating to GPS/INS."
"...recommended for personal and professional libraries."
This is an application-oriented book, which as such, does not include detailed mathematical derivations. It does provide Kalman filter algorithms (on floppy and in text), but if one needs the theory of Kalman filtering behind these, one needs to use a Kalman filtering text, such as Kalman Filtering Theory & Practice Using MATLAB (Second Edition), Wiley 2001, by Grewal and Andrews. The latter book gives all of the methods in square root filtering algorithms and derivations and more. If the "Asian Reviewer" is most interested in Kalman filtering, he/she would be better advised to buy a book on Kalman filtering.
GPS World Magazine reviewer recommends this book.......2001-10-12
Here are some quotes from a review of this book in GPS World, July 2001, pp 46-47, by Dr. John Angus, a consultant and researcher in the area of GPS-aided navigation systems, AND professor at Claremont Graduate University, Claremont, CA. Dr. Angus' credentials qualify him to review this book.
"Noteworthy is the comprehensiveness of the material on GPS, Kalman filtering and Kalman filter engineering, and the appendix on coordinate transforms...An instructor could easily develop a one-semester course on basic GPS or a full year course on GPS and inertial navigation, each of them "glued" together by the Kalman filter and enlivened by computer experiments with the MATLAB code provided."
"The writing...tends to be concise and the mathematics is kept to the minimum necessary to expose the theory and methods of filtering, GPS, and INS."
"...effectively addresses most of the basic engineering and performance issues relating to GPS/INS."
"...recommended for personal and professional libraries."
This is an application-oriented book, which as such, does not include detailed mathematical derivations. It does provide Kalman filter algorithms (on floppy and in text), but if one needs the theory of Kalman filtering behind these, one needs to use a Kalman filtering text, such as Kalman Filtering Theory & Practice Using MATLAB (Second Edition), Wiley 2001, by Grewal and Andrews. The latter book gives all of the methods in square root filtering algorithms and derivations and more. If the "Asian Reviewer" is most interested in Kalman filtering, he/she would be better advised to buy a book on Kalman filtering.
Almost completely useless book ..........2001-10-10
Of course the experience of the authors is great but none of it you can use either in your study or research. It is impossible to learn about Kalman filtering from this book as well as to improve your knowledge in this area. Book is intended for professionals in this area but professionals will not need it. Many intersting facts but no detailed information. For example one can know that the square root filtering method came from James Potter but there is nothing more about this method from this book. Otherwise you have to study sources of the software (included). Book is written as advertizing of author's skills and nothing else. Too much about nothing ...
Book Description
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.
Customer Reviews:
Lacking explanations as a textbook.......2004-02-11
I am trying to learn the subject by reading this and Gelb. Even though this book covers a lot of introductory concepts, it is lacking proper derivation of equations that I usually see in most math and physics textbooks. I find this book very disappointing for its price.
what you need to get started.......2003-07-05
I have read over simplified and over complicated descriptions
of the Kalman filter for years. The theoretical discussion is
well matched to the examples. THe authors have obviously had
extensive experiance TEACHING to a wide range of students and
the book benefits from their experiance.
I was able to program filters for three of the examples that
most closely match my own applications and exploit what I
learned in a matter of hours. The MATLAB code was useful, but
not critical.
what you need to get started.......2003-07-05
I have read over simplified and over complicated descriptions
of the Kalman filter for years. The theoretical discussion is
well matched to the examples. THe authors have obviously had
extensive experiance TEACHING to a wide range of students and
the book benefits from their experiance.
I was able to program filters for three of the examples that
most closely match my own applications and exploit what I
learned in a matter of hours. The MATLAB code was useful, but
not critical.
Best Kalman filter book.......2003-03-12
I use this book on a daily basis. It is worth its weight in gold.
Kalman filters, Brown & Hwang vs. Gelb.......2003-02-07
This is not my favorite text on Kalman filters. I find there is too much emphasis on elementary, preliminary material, and not enough on application.
I teach the subject out of my own notes (draft book) where the development follows that of Gelb, Applied Optimal Estimation, and all of the computations are done in Matlab. I first read Kalman's original papers in great detail, and rederived his work before the Gelb book (MIT Press, 1974) was published. Since the advdent of Matlab (1984) I have continued to used Gelb's derivations, and augmented that work with extensive Matlab examples.
I still find Gelb more usable as a text than other, newer books, and will continue to use it along with my Matlab supplements.
Average customer rating:
|
Maximum-Likelihood Deconvolution: A Journey into Model-Based Signal Processing (Signal Processing and Digital Filtering)
Jerry M. Mendel
Manufacturer: Springer
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Book Description
Convolution is the most important operation that describes the behavior of a linear time-invariant dynamical system. Deconvolution is the unraveling of convolution. It is the inverse problem of generating the system's input from knowledge about the system's output and dynamics. Deconvolution requires a careful balancing of bandwidth and signal-to-noise ratio effects. Maximum-likelihood deconvolution (MLD) is a design procedure that handles both effects. It draws upon ideas from Maximum Likelihood, when unknown parameters are random. It leads to linear and nonlinear signal processors that provide high-resolution estimates of a system's input. All aspects of MLD are described, from first principles in this book. The purpose of this volume is to explain MLD as simply as possible. To do this, the entire theory of MLD is presented in terms of a convolutional signal generating model and some relatively simple ideas from optimization theory. Earlier approaches to MLD, which are couched in the language of state-variable models and estimation theory, are unnecessary to understand the essence of MLD. MLD is a model-based signal processing procedure, because it is based on a signal model, namely the convolutional model. The book focuses on three aspects of MLD: (1) specification of a probability model for the system's measured output; (2) determination of an appropriate likelihood function; and (3) maximization of that likelihood function. Many practical algorithms are obtained. Computational aspects of MLD are described in great detail. Extensive simulations are provided, including real data applications.
Book Description
This book gives an introduction to the basic theory of stochastic calculus and its applications. Examples are given throughout the text, in order to motivate and illustrate the theory and show its importance for many applications in e.g. economics, biology and physics. The basic idea of the presentation is to start from some basic results (without proofs) of the easier cases and develop the theory from there, and to concentrate on the proofs of the easier case (which nevertheless are often sufficiently general for many purposes) in order to be able to reach quickly the parts of the theory which is most important for the applications. For the 6th edition the author has added further exercises and, for the first time, solutions to many of the exercises are provided.
Customer Reviews:
A very good book!.......2007-07-05
I read this book after I had read Karatzas' and Shreve's book "Stochastic Calculus..." and it is probably better to do it the other way round. The mathematical prerequisites are not high, however a good intuitive understanding of measure theory is probably necessary. The pace of the book is leasurely, the proofs are such, that pencil and paper is rarely needed, however no rigor is lost.
The book quickly moves to interesting applications of the theory, which is motivated very well.
It contains a few typographical errors, mostly in the last chapter, and mostly of a harmless nature.
With the necessary mathematical background, it seems to be an ideal introduction to this highly interesting topic of stochastic differential equations!
Excellent introduction on Stochastic Differential Equations.......2007-05-08
A well written book in Mathematics
Stochastic Differential Equations is a branch of mathematics. This book is not just for financial derivatives analysis or modeling. Oksendal first introduces the subject by raising a few stochastic problems (population growth; electric charge in RLC circuit; filtering problems, Dirichlet problems; asset management; optimal portfolio and options pricing) in the first chapter. The subsequent chapters develop notions and techniques which are able to solve wide varieties of stochastic problems (not just those mentioned in the first chapters). The arrangement is impressive in particular for readers who have no previous knowledge about the subject. The readers at least know the target for developing the techniques and would not lose the way when manipulating tons of symbols. Hints and answers to selected problems are invaluable to students for self-study.
To achieve a sound background on stochastic equations is extremely important especially in quantitative finance. It is not an easy job however. QF students may consider going through this book before seriously take Shreve's books on Stochastic Calculus for Finance.
OK intro to stochastic analysis.......2007-03-14
This is a standard work (it is the one I read when I first started looking at this sort of thing) but having taken it off the shelf recently again, I think it is overrated, for several reasons.
First, it is very notation heavy - TeX has seduced Mr. Oksendahl into all sorts of bad habits - I can very easily imagine that the earlier editions (mine is the 5th), which were written with a typewriter, are much more readable.
Second, the proofs are very formal, developed mostly in terms of classical functional analysis (square integrable real functions, geometry of real Hilbert spaces etc.). From the point of view of rigor this is fine, but from the point of view of intuition, not so much, esp. when combined with the heavyweight notation. In fact note that unless you have a decent background in functional analysis, of the sort you are more likely to pick up in a mathematics degree than a finance degree, then you are going to get precisely nowhere with this book.
I don't want to be too negative, and there is lots of good stuff here - just to warn that Oksendahl is not (as one might think) a royal road to the theory of SDEs (depressingly, it may be that Oksendahl is, nevertheless, the best of the bunch out there - it is certainly, all criticism not-withstanding, more accessible than Karatzas and Shreve).
Very good book - would not mind more on finance.......2007-02-08
Very good book. However the math prerequisite is at quite a high level. Especially the probability theory introduction could be a little less fast-paced. As my main interest was on the financial application I would not have minded a little more on that topic and a little less on e.g. filtering or stochatsic control in return.
good intro book.......2006-02-03
This is a good intro book. It brings you really fast to Ito's Formula and SDE. Somebody said that the Kolmogorov's backward eq in chapter 8 is wrong. This is false, it is just expressed in a different way than the usual form. However, with a change of time, you are all set.
Book Description
Problems in the motion control of aircraft are of perennial interest to the control engineer as they tend to be of complex and nonlinear nature.
Modelling and Control of Mini-Flying Machines is an exposition of models developed for various types of mini-aircraft:
- planar Vertical Take-off and Landing aircraft;
- helicopters;
- quadrotor mini-rotorcraft;
- other fixed-wing aircraft;
- blimps;
for each of which it propounds:
- detailed models derived from Euler-Lagrange methods;
- appropriate nonlinear control strategies and convergence properties;
- real-time experimental comparisons of the performance of control algorithms;
- review of the principal sensors, on-board electronics, real-time architecture and communications systems for mini-flying machine control, including discussion of their performance;
- detailed explanation of the use of the Kalman filter to flying machine localization.
To researchers and students in nonlinear control and its applications
Modelling and Control of Mini-Flying Machines provides valuable insights to the application of real-time nonlinear techniques in an always challenging area.
Book Description
Appropriate for upper-level undergraduates and graduate students, this volume addresses the fundamental concepts of martingales, stochastic integrals, and estimation. Written by an engineer for engineers, it emphasizes applications. Many theorems feature heuristic proofs; others include rigorous proofs to reinforce physical understanding. Numerous end-of-chapter problems enhance the book's practical value.
Average customer rating:
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Mathematics of Multidimensional Fourier Transform Algorithms (Signal Processing and Digital Filtering)
Richard Tolimieri ,
Myoung An , and
Chao Lu
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Book Description
Fourier transforms of large multidimensional data sets arise in many fields --ranging from seismology to medical imaging. The rapidly increasing power of computer chips, the increased availability of vector and array processors, and the increasing size of the data sets to be analyzed make it both possible and necessary to analyze the data more than one dimension at a time. The increased freedom provided by multidimensional processing, however, also places intesive demands on the communication aspects of the computation, making it difficult to write code that takes all the algorithmic possiblities into account and matches these to the target architecture. This book develops algorithms for multi-dimensional Fourier transforms that yield highly efficient code on a variety of vector and parallel computers. By emphasizing the unified basis for the many approaches to one-dimensional and multidimensional Fourier transforms, this book not only clarifies the fundamental similarities, but also shows how to exploit the differences in optimizing implementations. This book will be of interest not only to applied mathematicians and computer scientists, but also to seismologists, high-energy physicists, crystallographers, and electrical engineers working on signal and image processing. Topics covered include: tensor products and the fast Fourier transform; finite Abelian groups and their Fourier transforms; Cooley- Tukey and Good-Thomas algorithms; lines and planes; reduced transform algorithms; field algorithms; implementation on Risc and parallel
Average customer rating:
- Not suitable as a tutorial
- Better Summary Than Explanation
- Much too terse.
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Kalman Filtering: Theory and Practice
Mohinder S. Grewal , and
Angus P. Andrews
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Medieval Castles of Ireland
ASIN: 013211335X |
Book Description
The castles of Ireland, captivating in their number and variety, are an integral part of the story of medieval Europe. A lord's power and prestige were displayed in the majesty and uniqueness of his castle. The remains of several thousand castles enable us to reconstruct life in Ireland during these crucial centuries.
By weaving together physical evidence, Castles in Ireland tells the story of the nature and development of lordship and power in R isbn=0415925118 Ireland formed the setting to the interplay of the differing roles of competing lordships: English and Irish; feudal European and Gaelic; royal and baronial. Tom McNeill argues that the design of Irish castles contests the traditional view of Ireland as a land torn by wars and divided culturally between the English and Irish.
Customer Reviews:
Not suitable as a tutorial.......2004-09-13
The organization and content of the book doesn't lend itself to use as a tutorial. Heavy on equations/proofs and short on conceptual discussion. You'll need a graduate-school level of int/diff calculus, matrix algebra and statistics to get much out of this book, and that's only if you're interested in detailed derivations and historical perspective. I was hoping for something that would allow me to take the proofs "on faith" and get rapidly into implementation, but that's not in this book. I got a used copy for $2.50 so it was worth that, probably would have balked if it had been much more.
Better Summary Than Explanation.......2000-01-28
Don't look to this book as a satisfactory introduction to Kalman Filters. The authors seem to confuse summation with explanation -- this is a good review if you already know the material but it doesn't convey the concepts very well. I studied a 1993 edition of this book with Version 1.1 of the software and the Fortran source code that was provided was incomplete. I see from the author's review that new source code in C has been added since then so this may no longer be the case.
Much too terse........1997-01-10
The authors use non-traditional symbolism and do not always define symbols used. For example,
what is wring with the way Papoulis and Peebles define various statistical operators?
Changing what is so widely accepted does not make your presentation better. It just takes
longer to understand background subject matter and introduces unnecessary confusion into your final
topic - Kalman filters.
Book Description
This book presents a unified treatment of linear and nonlinear filtering theory for engineers, with sufficient emphasis on applications to enable the reader to use the theory. The need for this book is twofold. First, although linear estimation theory is relatively well known, it is largely scattered in the journal literature and has not been collected in a single source. Second, available literature on the continuous nonlinear theory is quite esoteric and controversial, and thus inaccessible to engineers uninitiated in measure theory and stochastic differential equations. Furthermore, it is not clear from the available literature whether the nonlinear theory can be applied to practical engineering problems. In attempting to fill the stated needs, the author has retained as much mathematical rigor as he felt was consistent with the prime objective—to explain the theory to engineers. Thus, the author has avoided measure theory in this book by using mean square convergence, on the premise that everyone knows how to average. As a result, the author only requires of the reader background in advanced calculus, theory of ordinary differential equations, and matrix analysis.
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