Approximate Kalman filtering / edited by Guanrong Chen.

Format:

Book

Contributor:

Chen, Quanrong.

Series:

Series in approximations and decompositions ; vol. 2.

Series in approximations and decompositions ; vol. 2

Language:

English

Subjects (All):

Kalman filtering.

Approximation theory.

Physical Description:

xiv, 226 pages : illustrations ; 23 cm.

Place of Publication:

Singapore ; River Edge, N.J. : World Scientific, [1993]

Summary:

Kalman filtering algorithm gives optimal (linear, unbiased and minimum error-variance) estimates of the unknown state vectors of a linear dynamic-observation system, under the regular conditions such as perfect data information; complete noise statistics; exact linear modeling; ideal well-conditioned matrices in computation and strictly centralized filtering.In practice, however, one or more of the aforementioned conditions may not be satisfied, so that the standard Kalman filtering algorithm cannot be directly used, and hence "approximate Kalman filtering" becomes necessary. In the last decade, a great deal of attention has been focused on modifying and/or extending the standard Kalman filtering technique to handle such irregular cases. It has been realized that approximate Kalman filtering is even more important and useful in applications.This book is a collection of several tutorial and survey articles summarizing recent contributions to the field, along the line of approximate Kalman filtering with emphasis on both its theoretical and practical aspects.

Notes:

Includes bibliographical references.

Includes index.

ISBN:

981021359X

OCLC:

28337684