Aerodynamic parameters compensation in the SINS/AMM/GNSS integrated navigation system

Considering the invalidation of the common airborne integrated navigation system caused by the satellite signal interference, this paper studies the new integrated navigation system, which utilizes the Aircraft Motion Model (AMM) to aid the MEMS-based low-accuracy Strap-down Inertial Navigation System (SINS). The new system operates as a backup airborne navigation method to improve the precision and reliability considerably. Two problems are studied in the paper: the precision problem that originates from the error of the aircraft's aerodynamic parameters, and the coupling problem that lies between the navigation system and the control system for the automatic aircraft. Therefore, the velocity matching of AMM and Global Navigation Satellite System (GNSS) is applied to compensate the aerodynamic parameters when the GNSS signal is stable. Meanwhile, the coupling problem is solved by switching from the automatic mode to manual mode intermittently. Based on a small-scaled fixed-wing Unmanned Aerial Vehicle (UAV) with propeller, the simulation tests show that the GNSS could be used to evaluate several key aerodynamic parameters of the longitudinal channel, thus improving the precision of the integrated navigation system.

[1]  Guillaume Ducard,et al.  Fault-tolerant Flight Control and Guidance Systems , 2009 .

[2]  Carlos Silvestre,et al.  Embedded UAV model and LASER aiding techniques for inertial navigation systems , 2010 .

[3]  Juan Garcia-Velo,et al.  Aerodynamic parameter estimation for high-performance aircraft using extended Kalman filtering , 1995 .

[4]  Frank Fresconi,et al.  Aerodynamic Characterizations of Asymmetric and Maneuvering 105-, 120-, and 155-mm Fin-Stabilized Projectiles Derived From Telemetry Experiments , 2011 .

[5]  D. Chilton Inertial Navigation , 1959, Nature.

[6]  Eugene A. Morelli,et al.  Aircraft system identification : theory and practice , 2006 .

[7]  Salah Sukkarieh,et al.  Vehicle Model Aided Inertial Navigation For A Uav Using Low-Cost Sensors , 2004 .

[8]  Morris M. Kuritsky,et al.  Inertial navigation , 1983, Proceedings of the IEEE.

[9]  Einar Berglund,et al.  Model-aided inertial navigation for underwater vehicles , 2008, 2008 IEEE International Conference on Robotics and Automation.

[10]  Nathan V. Hoffer,et al.  System identification of a small low-cost unmanned aerial vehicle using flight data from low-cost sensors , 2014 .

[11]  Christoph Eck,et al.  Navigation algorithms with applications to unmanned helicopters , 2001 .

[12]  3.2 Flight Control Systems................................. 6 , 2022 .

[13]  R. V. Jategaonkar,et al.  Aerodynamic parameter estimation from flight data applying extended and unscented Kalman filter , 2006 .

[14]  Troy S. Bruggemann,et al.  Investigation of MEMS inertial sensors and aircraft dynamic models in global positioning system integrity monitoring for approaches with vertical guidance , 2009 .

[15]  Mark Koifman,et al.  Inertial navigation system aided by aircraft dynamics , 1999, IEEE Trans. Control. Syst. Technol..