EKF-Based Trans-Lunar Coast Tracking

This project involved building an Extended Kalman Filter (EKF) to track a spacecraft's trajectory during its trans-lunar coast using measurements from NASA's Goldstone Deep Space Network. Key Achievements: • Designed and implemented a discrete-time EKF using a nonlinear two-body dynamics model with Gaussian white noise acceleration • Derived and implemented Jacobians for dynamic propagation and R3B measurement models to form EKF's sensitivity matrix • Created a full simulation pipeline in Python using real tracking data to estimate 6D spacecraft state and generate diagnostic plots Skills: Python, Extended Kalman Filter