Python implementation of a case study in Module 5 of the MITProfessionalX course "Data Science: Data to insights".
The case study is: "Module 2 Case Study - Kalman Filtering – Tracking Location of Object Moving with Constant Velocity". This case study is about tracking the state of an object moving with constant velocity, using Kalman Filtering, when we have noisy measurements of its velocity in 2 dimension.
Wikipedia for a primer on Kalman filters.
This project on github
This excellent youtube playlist on Kalman filtering