Kalman Filtering, 4th Edition

Preface to the Fourth Edition

This book is designed to provide our readers a working 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 fourth edition, we have added a new chapter on the attributes of probability distributions of importance in Kalman filtering, added two sections with easier derivations of the Kalman gain, added a section on a new sigmaRho filter implementation, updated the treatment of nonlinear approximations to Kalman filtering, expanded coverage of applications in navigation, added many more derivations and implementations for satellite and inertial navigation error models, and included many new examples of sensor integration. For readers who may need more background in matrix mathematics, we have included an Appendix B as a pdf file ...