Estimation, Control, and the Discrete Kalman Filter (Applied Mathematical Sciences, 71) - Hardcover

Catlin, Donald E.

Hardcover

ISBN 10: 038796777X ISBN 13: 9780387967776

Publisher: Springer, 1988

Synopsis

In 1960, R. E. Kalman published his celebrated paper on recursive min­ imum variance estimation in dynamical systems [14]. This paper, which introduced an algorithm that has since been known as the discrete Kalman filter, produced a virtual revolution in the field of systems engineering. Today, Kalman filters are used in such diverse areas as navigation, guid­ ance, oil drilling, water and air quality, and geodetic surveys. In addition, Kalman's work led to a multitude of books and papers on minimum vari­ ance estimation in dynamical systems, including one by Kalman and Bucy on continuous time systems [15]. Most of this work was done outside of the mathematics and statistics communities and, in the spirit of true academic parochialism, was, with a few notable exceptions, ignored by them. This text is my effort toward closing that chasm. For mathematics students, the Kalman filtering theorem is a beautiful illustration of functional analysis in action; Hilbert spaces being used to solve an extremely important problem in applied mathematics. For statistics students, the Kalman filter is a vivid example of Bayesian statistics in action. The present text grew out of a series of graduate courses given by me in the past decade. Most of these courses were given at the University of Mas­ sachusetts at Amherst.

Edition details

• Publisher: Springer
• Publication date: 1988
• Language: English
• ISBN 10: 038796777X
• ISBN 13: 9780387967776
• Binding: Hardcover
• Number of pages: 290