# The Mighty Kalman Filter

A Kalman Filter is an algorithm for estimating the state of a system from a series of noisy measurements. That’s what I was told, and it confused me. It also doesn’t really do the Kalman filter justice. If we have a bunch of noisy measurements of something why don’t we just take the mean and be done with it? Well the impressive part is estimating the state of a **system**. This is something that is changing. Let’s says we have a state. This is usually a collection of variables that completely describe where something is and what it’s doing. For example if we are considering a cricket ball hit by a batsman and flying through the air towards the boundary it has a state described by its position which could be three numbers (`x`

, `y`

, `z`

) and its velocity again (`vx`

, `vy`

, `vz`

). In addition the cricket ball is under the effect of gravity so there are forces influencing some of the state. We also assume...