The Kalman filter has become an essential tool in the fields of signal processing and system estimation. In this work, we delve deeply into advanced Kalman filtering, without addressing variants like the Extended Kalman Filter or Adaptive Kalman Filter, focusing solely on the theoretical background and practical applications of the advanced Kalman filter.

The Kalman filter is a powerful method for estimating the state of a system that changes over time, particularly in linear systems where its advantages are maximized. Advanced Kalman filtering explores the fundamental principles of the filter in greater depth, presenting various mathematical techniques and programming approaches to more accurately estimate system states. The goal of this book is to provide a clearer understanding of the sophisticated theory behind the Kalman filter and offer insights into its application to real-world problems.

Each chapter systematically explains the theoretical background, clarifies the mathematical details, and supports understanding with real code examples. In particular, we will discuss in-depth the detailed implementation and optimization techniques of algorithms for solving complex problems. Through this, readers will be equipped to autonomously perform high-level applications of the Kalman filter.

I hope this book helps you gain in-depth knowledge of advanced Kalman filtering and apply it to real systems, assisting in solving problems. In this rapidly evolving field, I look forward to you gaining new insights and building a more robust technical understanding on this journey.