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# Extended Kalman Filter Project Starter Code
Self-Driving Car Engineer Nanodegree Program

In this project you will utilize a kalman filter to estimate the state of a moving object of interest with noisy lidar and radar measurements.
This project involves the Simulator which can be downloaded [here](https://github.com/udacity/self-driving-car-sim/releases)

This repository includes two files that can be used to set up and install [uWebSocketIO](https://github.com/uWebSockets/uWebSockets) for either Linux or Mac systems. For windows you can use either Docker, VMware, or even [Windows 10 Bash on Ubuntu](https://www.howtogeek.com/249966/how-to-install-and-use-the-linux-bash-shell-on-windows-10/) to install uWebSocketIO. Please see the uWebSocketIO Starter Guide page in the classroom within the EKF Project lesson for the required version and installation scripts.

Once the install for uWebSocketIO is complete, the main program can be built and run by doing the following from the project top directory.

1. mkdir build
2. cd build
3. cmake ..
4. make
5. ./ExtendedKF



INPUT: values provided by the simulator to the c++ program

["sensor_measurement"] => the measurement that the simulator observed (either lidar or radar)


OUTPUT: values provided by the c++ program to the simulator

["estimate_x"] <= kalman filter estimated position x
["estimate_y"] <= kalman filter estimated position y
["rmse_x"]
["rmse_y"]
["rmse_vx"]
["rmse_vy"]

---

## Other Important Dependencies

* cmake >= 3.5
  * All OSes: [click here for installation instructions](https://cmake.org/install/)
* make >= 4.1 (Linux, Mac), 3.81 (Windows)
  * Linux: make is installed by default on most Linux distros
  * Mac: [install Xcode command line tools to get make](https://developer.apple.com/xcode/features/)
  * Windows: [Click here for installation instructions](http://gnuwin32.sourceforge.net/packages/make.htm)
* gcc/g++ >= 5.4
  * Linux: gcc / g++ is installed by default on most Linux distros
  * Mac: same deal as make - [install Xcode command line tools](https://developer.apple.com/xcode/features/)
  * Windows: recommend using [MinGW](http://www.mingw.org/)

## 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 `

## Editor Settings

We've purposefully kept editor configuration files out of this repo in order to
keep it as simple and environment agnostic as possible. However, we recommend
using the following settings:

* indent using spaces
* set tab width to 2 spaces (keeps the matrices in source code aligned)


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EKF to estimate the state moving object through LIDAR and RADAR data

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