Aerodynamic Parameter Estimation for a Scaled F-16: A Simulation-Based Sensitivity Analysis

System identification is a technique used to define an unknown system based on its input and output. This research focuses on utilizing simulated flight data to analyze the effects of various errors and assumptions on the resulting aerodynamic model. The results are analyzed to determine which sources of error and assumptions have the greatest effect on the aerodynamic model. The analysis shows that simplifying model assumptions and failing to account for actuator dynamics introduce the most significant errors. Specifically, the total velocity cannot be estimated by using just the pitot tube measurement, as the corrupted dynamic pressure calculations result in unacceptable errors in the non-dimensional rates. Additionally, using the commanded control inputs instead of the actual actuator positions led to substantial unacceptable errors in the identified control derivatives. While sensor noise also degrades the model, its effects do not have a large impact on the entire model. The accelerometer noise primarily impacted force coefficients, and the gyroscope noise severely affected the moment coefficients. The analysis of the various errors highlights the necessity of measuring or accurately estimating both the full velocity vector and the actual control surface deflections. The results inform critical decisions in developing a successful flight test and determining the necessary measurements or sensing device accuracy for a successful system identification study.