ahany / extended-kalman-filter

Extended Kalman Filter using LIDAR and RADAR measurements for pedestrian tracking

Extended Kalman Filter Project

Self-Driving Car Engineer Nanodegree Program

This project implements an extended Kalman filter in C++. The input is in the form of simulated lidar and radar measurements detecting a bicycle that travels around a vehicle. The objective is to use a Kalman filter, the lidar measurements and the radar measurements to track the bicycle's position and velocity.

This project requires Udacity Simulator which provides the inputs to the Kalman filter.

Dependencies

• cmake >= 3.5
• make >= 4.1
• gcc/g++ >= 5.4

Basic Build Instructions

1. Clone this repo.
2. Make a build directory: mkdir build && cd build
3. Compile: cmake .. && make
   • On windows, you may need to run: cmake .. -G "Unix Makefiles" && make
4. Run it: ./ExtendedKF

Files in src Folder

main.cpp - communicates with Udacity Simulator receiving data measurements, calls a function to run the Kalman filter, calls a function to calculate RMSE.

FusionEKF.cpp - initializes the filter, calls the predict function, calls the update function.

kalman_filter.cpp- defines the predict function, the update function for lidar, and the update function for radar.

tools.cpp- function to calculate RMSE and the Jacobian matrix.