Extended Kalman Filter Project Starter Code
Self-Driving Car Engineer Nanodegree Program
This project implements Extended Kalman filter to estimate position and velocity of a moving pedestrian. The state of a moving object of interest with noisy lidar and radar measurements. In order to satisfy the project rubric requirements, EKF with RMSE below the pre-defined bound has been devised.
This project should be run in the Simulator which can be downloaded here
Cmake is used as a build system for the project. In order to compile the code:
- mkdir build
- cd build
- cmake ../src/
- make
- ./ExtendedKF
Important Dependencies
The project has been tested / run on Ubuntu.
- cmake >= 3.5
- make >= 4.1 (Linux, Mac),
- gcc/g++ >= 5.4
RMSE
The Extended Kalman filter is run against the test data set, obtaining the following error:
In order to come to a correct results:
- initialize previous time stamp when seeing the first time stamp;
- update for Radar: (1) roll the angle to
[-pi, pi]
interval after calculatingy
- update for Radar: (2) avoid infinitesimal numbers when calculating rho ( or h(0) ), in order to avoid division by zero in rho_dot (or h(2) ).