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Team Status Report 3/7

This week, our team continued development of both the hardware and software components of the celestial positioning system. On the hardware side, we continued configuring the onboard compute platform and sensor interfaces so that camera and IMU data can be reliably streamed into the processing pipeline. On the software side, we made progress on several key algorithmic components including the celestial feature detection pipeline and the state estimation framework that will fuse inertial and visual measurements.

Our current focus is on ensuring that the different subsystems can operate together as a complete navigation pipeline. The camera system is being prepared for reliable star detection under nighttime conditions, while the estimation framework is being implemented to fuse IMU propagation with celestial observations. These components together will allow the system to produce stable position estimates even when GPS signals are unavailable.

In the upcoming week, we plan to continue refining the visual feature extraction pipeline and integrate the estimator with the outputs of the celestial solver. As additional hardware arrives, we will begin collecting test data to evaluate system performance under realistic conditions.

A: Our celestial positioning system is designed to address the global need for reliable navigation in environments where GPS signals are unavailable or unreliable. GPS denial can occur in many contexts worldwide, including remote regions with limited infrastructure, areas affected by signal interference or jamming, and environments where satellite visibility is obstructed.

C: As designed, our system is designed for repeated-use on UAVs for global positioning. It uses standard electronic components, and thus doesn’t pose any additional risk of pollution or damage to the environment more than a drone does without it. While our initial prototype will feature a 3D-printed PLA carrier board for rapid iteration, we will attempt to make our final carrier board metal which will structurally strengthen the module but also decrease negative environmental impact.

A written by Eddie, B written by Rachel, C written by Julius.

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Eddie’s Status Report 3/7

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.