Modeling and Evaluation of UAV Navigation Using IMU-GPS Sensor Fusion

Unmanned Aerial Vehicle (UAV) systems are inherently complex, requiring precise synchronization of sensors, actuators, and control algorithms to ensure stable and efficient flight. Accurate estimation of navigation states, particularly attitude and angular rates are critical for flight stability and control. However, achieving robust state estimation remains challenging due to sensor limitations, external disturbances, and system uncertainties. This study presents a comprehensive modeling and simulation framework for UAV navigation, integrating Inertial Measurement Unit (IMU) and Global Positioning System (GPS) sensor fusion using Simulink. The IMU and GPS measurements are simulated during flight to assess their individual and combined contributions to heading and attitude estimation. Simulation verification demonstrates the comparative performance of the employed estimation techniques, highlighting their advantages and limitations in real-world applications.