Integrated State Estimation Development for Actively Controlled Rockets

This paper details the development process of an inertial navigation system to support a collegiate team's actively controlled jet vanes rocket development efforts. Precise and accurate estimation of the rocket's position, velocity, and attitude are required for successful active feedback controls, validation of the team's in-house 6-DOF simulations, and ensuring reliable real-time state transition detection. First, sensor models are used to convert a 6-DOF reference trajectory to sensor readings. Next, these tools are fed into a ground-based static Kalman Filter for sensor bias and initial attitude determination (IAD), along with an in-flight Extended Kalman Filter for translational and attitude estimation. Validation of these algorithms in simulations were performed with Monte Carlo analysis in MATLAB on multiple trajectories and sensor parameters. Lastly, the algorithms were implemented on a custom flight computer in the STM32 embedded C environment and details the solutions to any practical implementation issues encountered. The paper establishes a step-by-step process of designing a navigation architecture from whiteboard to real-time flight, with performance analysis included.