- Assignment Details:
https://github.com/syedjameel/Kalman-Filter-GPS-Accelerometer/blob/6a83dc962ac21bf934f1e027bb3cb2005e558399/HW2_Kalman%20Filter_v2.pdf
To Create simplified recursive filter and compare its results with 1D Kalman filter
- Generate noisy 1D data,
- Demonstrate 1D Linear Kalman Filter estimation on data,
- Create simplified recursive filter and compare its results with 1D Kalman filter
- Play with different values for filter initialization (xOpt and eOpt) to prove the Filter convergence
Kalman Filter - Estimation of the traveled distance
- To predict the traveled distance based on the linear accelerometer measurement. Update the predicted value using the distance measurements of the GPS sensor.
- Apply Kalman filter to predict the traveled distance and plot the graphs of the measured distance (in meters) and the predicted distance (in meters)
This Assignment is run by a single notebook file main.ipynb
in the main folder.
- Clone project using command:
https://github.com/syedjameel/Kalman-Filter-GPS-Accelerometer.git
-
Run the following command to navigate to the directory using:
cd SPA-Assignment-2/
-
Run the following command to install dependent libraries:
pip3 install -r requirements.txt
-
Finally, Run the
main.ipynb
file [InJupyter notebook
orcolab
]