This book is designed to provide familiarity with both the theoretical and practical
aspects of Kalman filtering by including real-world problems in practice as illustrative
examples. The material includes the essential technical background for Kalman filtering
and the more practical aspects of implementation: how to represent the problem in
a mathematical model, analyze the performance of the estimator as a function of
system design parameters, implement the mechanization equations in numerically
stable algorithms, assess its computational requirements, test the validity of results,
and monitor the filter performance in operation. These are important attributes of
the subject that are often overlooked in theoretical treatments but are necessary for
application of the theory to real-world problems.
In this third edition, we have included important developments in the implementation
and application of Kalman filtering over the past several years, including adaptations
for nonlinear filtering, more robust smoothing methods, and developing
applications in navigation.