Worked on the ISSUIUC/MIDAS-Software repository to enhance flight dynamics and state estimation for aerospace applications. Focused on improving estimation accuracy by conditioning gravity application based on rocket flight state and refactoring aerodynamic coefficient data to support future spline interpolation. Simplified the Kalman filter’s state transition matrix by removing aerodynamic and mass-dependent terms, delegating their integration to other components for cleaner architecture. Utilized C++ and embedded systems expertise to prepare a data pipeline that enables smoother updates in state estimation. The work addressed maintainability and set the groundwork for data-driven aerodynamic modeling using Kalman filters and advanced interpolation techniques.