syedjameel/kalman-filter-gps-accelerometer

SPA Assignment-1

• Assignment Details:

https://github.com/syedjameel/Kalman-Filter-GPS-Accelerometer/blob/6a83dc962ac21bf934f1e027bb3cb2005e558399/HW2_Kalman%20Filter_v2.pdf

Task 1

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

Task 2

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)

Description:

This Assignment is run by a single notebook file main.ipynb in the main folder.

Local Setup

• Clone project using command:

https://github.com/syedjameel/Kalman-Filter-GPS-Accelerometer.git

How to Run

1. Run the following command to navigate to the directory using:

   cd SPA-Assignment-2/ 

2. Run the following command to install dependent libraries:

   pip3 install -r requirements.txt

3. Finally, Run the main.ipynb file [In Jupyter notebook or colab]