This week, I focused on beginning implementation of the Extended Kalman Filter for our positioning system. I set up the filter structure in code, including the state representation, prediction step using IMU acceleration, and covariance propagation. I also started implementing the measurement update step that will incorporate celestial position estimates to correct inertial drift. Currently, I am testing the filter framework using simulated data to verify that the prediction and update steps behave correctly.
My progress is on schedule. The main goal for this phase was to begin coding the estimation algorithm, and I now have the core filter structure in place.
Next week, I plan to complete testing of the filter, tune the noise parameters, and prepare the implementation to accept real IMU and celestial solver data once the hardware is ready.