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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.
- Sales Rank: #796518 in Books
- Published on: 1996-11-28
- Ingredients: Example Ingredients
- Original language: English
- Number of items: 1
- Dimensions: 10.30" h x 1.11" w x 7.24" l, 1.98 pounds
- Binding: Paperback
- 496 pages
Most helpful customer reviews
0 of 0 people found the following review helpful.
Four Stars
By Dyl
Lots of theorems. Decently written although sometimes more confusing than necessary.
9 of 10 people found the following review helpful.
what you need to get started
By K. McLaughlin
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.
30 of 31 people found the following review helpful.
Excellent Intro to KF, easy on the rigor..
By A Customer
This is the third edition of an introductory text on Kalman Filtering. It is easy to read, easy to follow: it presents the discrete-time and the continuous-to-discrete KFs in a clear and logical manner. The MATLAB exercises didn't seem to be integrated with the text too well, and they were written in MATALB v 4., so there are a few "corrections" that must be made ("randn" in v. 5, so all the references to "rand" in the MATLAB code must be fixed). The extended KF and some implementation issues (UDU filter, sequential estimation) are not covered as well as other topics. If you are new to the topic and are looking for a good introduction this is the book. If you already know the topic, I'd pass on the text. What I'd like to see is a new edition of Gelb, replete with MATLAB implementations..
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