methods based on Kalman filtering models, including more recent, more robust
implementations. Chapter 7 is devoted to nonlinear applications, including extended
Kalman filters for quasilinear problems, and to sampling-based methods for extending
Kalman filtering to more highly nonlinear problems. Applications of these techniques
to the identification of unknown parameters of systems are given as examples.
Chapter 6 covers the more modern implementation techniques, with algorithms
provided for computer implementation.
Chapter 8 deals with more practical matters of implementation and use beyond the
numerical methods of Chapter 7. These matters include memory and throughput
requirements (and methods to reduce them), divergence problems (and effective remedies),
and practical approaches to suboptimal filtering and measurement selection.
As a demonstration of how to develop and evaluate applications of Kalman filtering,
in Chapter 9 we show how to develop different Kalman filtering configurations for integrating
global navigation satellite system receivers with inertial navigation systems.
Chapters 4–8 cover the essential material for a first-year graduate class in Kalman
filtering theory and application or as a basic course in digital estimation theory and
application.