The 4th Edition to the Introduction of Random Signals and Applied Kalman Filtering is updated to cover innovations in the Kalman filter algorithm and the proliferation of Kalman filtering applications from the past decade. The text updates both the research advances in variations on the Kalman filter algorithm and adds a wide range of new application examples.

Several new chapters have been created by reducing, combining and restructuring older material, with the goal of making the introductory background material more accessible to readers. New sections include: Mathematical description of Random Signals and Linear Systems; State-Space Modeling and Monte Carlo Simulation; Derivation of the Basic Kalman filter algorithm; and Alternative forms of the Kalman filter. Several of these chapters include a significant amount of new material on applications such as simultaneous localization and mapping for autonomous vehicles, inertial navigation systems and global satellite navigation systems.