Air Data Estimation by Fusing Navigation System and Flight Control System

Abstract

A novel synthetic air data estimation method without using air data sensors is presented, and the method only relies on the information from the Navigation System (NS) and Flight Control System (FCS). The aircraft's aerodynamic model is also required to make a connection between the FCS control parameters and the NS measurements. The airspeed, angle of attack and sideslip, angular velocity and wind speed are defined as state vectors, and state equations are established through the aircraft's aerodynamic model and dynamics. Linear velocity and angular velocity provided by the navigation system are considered as the measurement vector. To deal with variable wind fields, a novel Initialised Three-step Extended Kalman Filter (ITEKF), which considers the wind speed as an unknown input, is developed to track the variation of wind speed. Simulation results based on a Generic Hypersonic Vehicle (GHV) model are presented and compared with an existing method. Factors affecting the method's accuracy include the navigation system accuracy and the aerodynamic model error, are also discussed.

An innovative analytic redundancy approach to air data sensor fault detection

“…In this section, a simple and reliable air data estimation method is presented combining the IMU, NSD, and aircraft kinematics. The air data mathematical model used for filtering in this paper differs from that of Lu (2018) (22) , which used rotational rates as states, and attitude angles from the NSD as measurements. In this method, the rotational rates and linear accelerations considered as inputs and NSD-calculated ground velocities and attitude angles are considered as measurements.…”

“…Since the performance of an FDI algorithm highly depends on the estimation algorithm, the non-linear estimators are preferable among other approaches. Most recently, an air data estimation method was proposed using the navigation system and flight control system information (22) . This has proved the validity of using onboard INS/GPS navigation system data to estimate air data parameters without considering the conventional air data probe-based air data measurements.…”

A novel INS/ADS integrated navigation method based on INS error model-aided unbiased converted measurement

“…The AOA denotes the angle between the projection of the sum velocity vector on the plane of symmetry and the chord line. The AOS denotes the angle between the sum velocity vector and the plane of symmetry [9,10]. The shaded area represents the plane of symmetry of the aircraft.…”

“…The conventional measurement conversion method is as follows. In the first step, the TAS of ADS is converted to the velocity vector in the body-frame using the AOA and the AOS [9,10]:…”

“…Unfortunately, the satellite signals are prone to be affected by the external environments [7], such as radio interferences, multi-path reflections and so on [8]. The air data system (ADS) can provide true airspeed (TAS), angle of attack (AOA), angle of sideslip (AOS) and atmosphere pressure altimeter [9], which has unparalleled advantages of noncumulative errors and not being interfered by external signals [10]. The air data inertial reference unit researched by Honeywell [11] is composed of INS and ADS, which is widely used in large civil aircraft [12].…”