Extended Kalman Filter Implementation for Three-Attitude-Angle Fusion

The integration of triaxial gyroscope and triaxial accelerometer signals using Extended Kalman Filter (EKF) for three-attitude-angle fusion finds extensive applications in modern aviation. By combining angular rate measurements from gyroscopes and acceleration data from accelerometers, precise positioning and navigation can be achieved in aircraft, rockets, and satellites. The Extended Kalman Filter enhances fusion accuracy and stability through its prediction-correction mechanism, where the system first predicts states using gyroscope data and then corrects them using accelerometer measurements. Implementation typically involves defining state vectors (containing roll, pitch, yaw angles), measurement models incorporating gravitational acceleration components, and Jacobian matrices for linearization. This technique extends beyond aviation to ground transportation, marine exploration, and robotics applications, where sensor fusion algorithms handle nonlinear systems through iterative prediction-update cycles while managing process and measurement noise covariance matrices.