git clone https://github.com/dhruvpatel44/EKF.git
In this project, we look at how one-dimensional Kalman Filter works. The problem we would look over in this project can be thought of as a target tracking problem in one-dimensional space.
Here's how the files are laid out.
EKF.pdf : : To understand the basics of how Extended Kalman Filter works, the theory behind it and the problem statement with relevant equations.
ekf.py : : The code
true_odometry.csv | sensor_odom.csv : : These are the data files that will be used in running the code. They represents the True Data without any noise (representing a perfect world - which will be used to compare our estimated states) and Sensor Data with added noise (representing real-world equivalent - which will be used as measurement taken from a sensor).