A Kalman Filter Primer

With its mathematically rigorous, "no frills" approach to the basic discrete-time Kalman filter, A Katman Filter Primer builds a thorough understanding of the inner workings and basic concepts of Kalman filter recursions from first principles. Instead of the typical Bayesian perspective, the author develops the topic via least-squares and classical matrix methods using the Cholesky decomposition to distill the essence of the Kalman filter and reveal the motivations behind the choice of the initializing state vector. He supplies pseudo-code algorithms for the various recursions, enabling code development to implement the fitter in practice.

A unique and ideal introduction, A Kalman Filter Primer...

• Provides a concise, self-contained treatment of the Kalman filter, from first principles to code development, that is easily approachable by the non-statistician
• Uses a simple, easily accessible framework that avoids notationa) overload and extraneous details
• Presents complete proofs for every major result, endowing a fundamental understanding of the mathematics involved
• Includes pseudo-code algorithmic summaries throughout the text