Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises, 4th Edition

Preface To The Fourth Edition

We are happy to report that Kalman filtering is alive and well after 50 years of existence. New applications keep appearing regularly which broadens the interest throughout engineering. This, of course, has all been made possible by the fantastic advances in computer technology over the past few decades. If it were not for that, the neat recursive solution for the Wiener filter problem that R. E. Kalman introduced in 1960 would probably only be remembered as an interesting academic curiosity, in engineering literature at least. Enough of the history; clearly, Kalman filtering is here to stay. It is eminently practical, and it has withstood the test of time.

This text is a revision of the Third Edition of Introduction to Random Signals and Applied Kalman Filtering with MATLAB Exercises. Kalman filtering has now reached a stage of maturity where a variety of extensions and variations on the basic theory have been introduced since the Third Edition was published in 1997. We have included some of these developments, especially those that deal with nonlinear systems. The extended Kalman filter is included because it is used widely and it is still the preferred solution to many integrated navigation systems today, just as it was a few decades ago.

Our intent is still to keep the book at the introductory level with emphasis on applications. We feel that this material is suitable for undergraduate as well as beginning graduate courses. The necessary prerequisite ...