Kalman Filter from the Ground Up, 3rd edition

The Kalman Filter is an algorithm for estimating and predicting the state of a system in the presence of uncertainty, such as measurement noise or unknown influences of external factors. The Kalman Filter is an essential tool in areas like object tracking, navigation, robotics, and control. For instance, it can be applied to estimate the computer mouse trajectory by reducing noise and compensating for hand jitter, resulting in a more stable motion path. In addition to engineering, the Kalman Filter finds applications in financial market analysis, such as detecting stock price trends in noisy market data, and in meteorological applications for weather prediction. 

Although the Kalman Filter is a simple concept, many educational resources present it through complex mathematical explanations and lack real-world examples or illustrations. This gives the impression that the topic is more complex than it actually is. Kalman Filter from the Ground Up presents an alternative approach that uses hands-on numerical examples and simple explanations to make the Kalman Filter easy to understand. It also includes examples with bad design scenarios where Kalman Filter fails to track the object correctly and discusses methods for correcting such issues. MATLAB is introduced and used to solve numerous examples in the book. In addition, a supplemental set of MATLAB code files is available for download.

By the end, you will not only understand the underlying concepts and mathematics but also be able to design and implement the Kalman Filter on your own.