A novel INS/GPS fusion architecture for aircraft navigation

In this paper, we address the issue of aircraft navigational state estimation from the perspective of (i) aircraft attitude estimation, also called as the attitude heading reference system (AHRS), and (ii) estimating the full inertial solution of the aircraft (position, velocity & attitude), also known as inertial navigation system-global positioning system (INS/GPS) fusion, in the presence of accelerometer and gyroscopic bias. A suite of nonlinear filters; two Kalman filter (KF) based - extended and unscented Kalman filter (EKF, UKF) and a non-KF based filter that is the nonlinear complementary filter (NCF) on the μμ(3) group, are studied and evaluated for the AHRS. In this paper we propose a novel INS/GPS fusion architecture that demonstrated a significant improvement in performance over the conventional KF based schemes, in tests done on realistic simulated aircraft data. In the proposed architecture, the attitude estimation is decoupled from the position and velocity estimation, by exploiting the NCF as it is known for its superior attitude and gyroscopic bias estimation performance. The position and velocity estimation is carried out by a conventional EKF. The crucial difference between KF based schemes and the NCF for attitude estimation is in the generation of the measurement set, which involves trigonometric inverses and are susceptible to singularities for KF based schemes, which the NCF avoids. Furthermore, the NCF algorithm is faster and computationally more efficient than a KF algorithm scheme since the NCF does not involve the computation of matrix inverses like KF based schemes.