This is a step-by-step code for understanding Discrete Kalman Filters that I used for the Computer Science classes I taught. The goal is not to provide an optimal code, but to provide an understanding of how the process works.
The recommended order for analysis is:
- kalman_simple_1D.py
- kalman_simple_1D_iterations.py
- kalman_simple_1D_loop.py
- observation_matrix_example.py
- prediction_step_example.py
- state_matrix_example.py
- complete_kalman_example.py