Fundamentals of Kalman Filtering: A Practical Approach (Progress in Astronautics and Aeronautics, 232)

This practical text demonstrates by example how to build Kalman filters and shows how the filtering equations can be applied to real-life problems. Computer code written in FORTRAN, MATLAB, and True BASIC accompanies all of the examples. Unlike other texts on Kalman filtering, the book does not devote any time to derivations; instead, Kalman filtering equations are explained in simple terms, and most of the text is dedicated to applying Kalman filtering to actual problems. All background and numerical techniques for understanding concepts is presented in the first chapter. Because real-life problems are seldom presented in the form of differential equations, a great deal of time is spent setting up a problem before the Kalman filter is actually formulated, to give the reader an intuitive feel for the problem being addressed. The authors illustrate several different filtering approaches for tackling a specific problem, so that readers can gain experience in software and performance tradeoffs for determining the best filtering approach. This third edition offers three new chapters on fixed- or finite-memory filters, use of the chain rule from calculus for filter initialization, and use of a bank of linear sine-wave Kalman filters for estimating the actual frequency of noisy sinusoidal measurements. An appendix serves as a central location for key concepts and formulas. Zarchan is affiliated with the technical staff at MIT Lincoln Laboratory. Musoff was affiliated with the Charles Stark Draper Laboratory Annotation ©2009 Book News, Inc., Portland, OR (booknews.com)

Paul Zarchan has a BSEE degree from the City College of New York and an MSEE degree from Columbia University. He has more than 30 years' experience in the missile guidance and control field and has worked as Principal Engineer for Raytheon, served as Senior Research Engineer with the Israeli Ministry of Defense and is currently a Principal Member of the Technical Staff at the Charles Stark Draper Laboratory.

Dr. Howard Musoff has a BSEE degree from the City College of New York, an MSEE degree from Northeastern University, and an Sc.D.degree from MIT. He is a Principal Member of the Technical Staff at the Charles Stark Draper Laboratory, were he has been employed for more than 40 years. Among other tasks, he designs Kalman filters for applications in the filed of inertial navigation. Dr. Musoff is also a co-holder of two patents in that field.