This week, I continued developing the state estimation framework for our celestial positioning system. I expanded the Extended Kalman Filter implementation to better handle the interaction between inertial measurements and visual updates from the celestial solver. In particular, I worked on structuring the filter so that the IMU propagates the system state at a higher rate while the visual pipeline provides lower-frequency corrections. I also began testing the filter behavior with simulated measurements to evaluate how well the estimator corrects drift when intermittent celestial observations are available.
My progress is currently on schedule. The main objective this week was to refine the estimator structure and verify that the propagation and update steps behave consistently when combining inertial and visual information. Initial tests suggest that the filter framework is functioning as expected.
Next week, I plan to further tune the noise parameters and integrate the estimator interface with the outputs of the visual pipeline so that the filter can begin processing real data once the hardware and sensing pipeline are fully operational.