Explore the fundamentals of Kalman Filters in this comprehensive video lecture, the first part of a three-part series. Begin with an introduction to recursive filters, including average, moving average, and low-pass filters. Learn through practical MATLAB examples that demonstrate real-world applications. Gain insights into the basics of the Kalman Filter algorithm and its importance in estimation and data analysis. Discover how to apply these concepts to dynamic attitude estimation using gyroscope data. Access accompanying MATLAB code and lecture notes to enhance your learning experience. Perfect for beginners looking to build a strong foundation in Kalman Filters and their applications in aerospace engineering and beyond.