Sensor Fusion using Unscented Kalman Filter

In this project utilize an Unscented Kalman Filter to estimate the state of a moving object of interest with noisy lidar and radar measurements.

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

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

Other Important Dependencies

  • cmake >= v3.5
  • make >= v4.1
  • gcc/g++ >= v5.4

Basic Build Instructions

  1. Clone this repo.
  2. Make a build directory: mkdir build && cd build
  3. Compile: cmake .. && make
  4. Run it: ./UnscentedKF Previous versions use i/o from text files. The current state uses i/o from the simulator.

Code Style

Please stick to Google’s C++ style guide as much as possible.

Noise parameter tunning

The longitudinal acceleration noise and yaw acceleration noise standard deviations are tunned for the both the data set to meet an optimal NIS values. The plots of the NIS values for lidar and radar sensor can be download at the following path.

LIDAR

RADAR