Extended-Kalman-Filter

Udacity CarND Term 2, Project 1 - Extended Kalman Filters

Project Basics

In this project, I used C++ to write a program taking in radar and lidar data to track position using Extended Kalman Filters.

The code will make a prediction based on the sensor measurement and then update the expected position. See files in the 'src' folder for the primary C++ files making up this project.

Build instructions

Assuming you have 'cmake' and 'make' already:

1. Clone this repo.
2. Make a build directory: mkdir build && cd build
3. Compile: cmake .. && make
4. Run it: ./ExtendedKF

Results

In two different simulated runs, my Extended Kalman Filter produces the below results. The x-position is shown as 'px', y-position as 'py', velocity in the x-direction is 'vx', while velocity in the y-direction is 'vy'. Residual error is calculated by mean squared error (MSE).

Test One

Test Two