Kalman Filter Explained!

The local beach is not far from where I live, so sometimes I go there to enjoy my solitude. Today I was meditating on tomorrow’s lecture on Kalman Filter. “It could be a challenging concept for some students”, I said to myself. I sat on a large rock, felt the gentle breeze, and soaked in the warm sunset. I watched the seagulls flying over the majestic sunset, casting fuzzy reflections on the sparkling ocean. Suddenly I have an indescribable joyful moment — the line of the flying seagull in the sky and the fuzzy reflections on the ocean is a beautiful analogy for the Kalman Filter. I shouted to the seagulls “A-ha”, and they echoed me with “A-ha-A-ha-A-ha”.

If this is the first time you've heard of the Kalman Filter, you may not know that numerous devices in our lives have relied on it. The Kalman Filter estimates the trajectory of a moving object. Your iPhone or Android phone has a map app that estimates the location of the phone and driving distance. Cars, fleet trucks, ships, aircraft, or drones have the GPS (Global Positioning System) to track movement with more accuracy. A famous early use was the Apollo navigation computer that took Neil Armstrong to the moon and, most importantly, brought him back. The Kalman Filter also is widely applied in time series anomaly detection. With the advent of computer vision to detect objects in motions such as cars or baseball curves, the Kalman Filter model will…