: The book starts by explaining how a simple average can be calculated recursively, which is the foundational "mental model" for the Kalman Filter. Part I: Simple Filters : Covers basic concepts like the Moving Average Filter First-Order Low-Pass Filter using real-world examples like sonar and stock prices. Part II: The Kalman Filter Theory
The Kalman filter is a recursive algorithm that estimates the state of a system from noisy measurements. It uses a combination of prediction and measurement updates to estimate the state of the system. The algorithm is based on the following assumptions: : The book starts by explaining how a