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Utilize an Extended Kalman Filter to estimate the state of a moving object of interest with noisy Lidar and Radar measurements

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Extended Kalman Filter Project

Overview

This project utilizes a kalman filter to estimate the state of a moving object of interest with noisy lidar and radar measurements. Radar measurements are non-linear and the extended Kalman filter (EKF) is the nonlinear version of the Kalman filter which linearizes about an estimate of the current mean and covariance. This project is a fusion of linear Lidar and non-linear Radar measurements.

Dependencies

  • cmake >= 3.5
  • All OSes: click here for installation instructions
  • make >= 4.1
    • Linux: make is installed by default on most Linux distros
  • gcc/g++ >= 5.4
    • Linux: gcc / g++ is installed by default on most Linux distros

Build Instructions

  1. Clone the Extended Kalman Filter git repository
    $ git clone https://github.com/jfoshea/Extended-Kalman-Filter.git
    
  2. Make a build directory if it does not exist
    $ mkdir build && cd build 
    
  3. Compile
    $ cmake .. && make 
    
  4. Run Extended Kalman Filter
    $ ./ExtendedKF 
    

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Utilize an Extended Kalman Filter to estimate the state of a moving object of interest with noisy Lidar and Radar measurements

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