Tien Dang Nguyen


This paper presents a novel adaptive method for attitude estimation of unidentified flying object based on acceleration sensors and gyroscope sensors. Because the external acceleration is the main error source of estimation error. Therefore, in this paper, we proposed a new method, in which the extended Kalman filter is combined with compensating external acceleration to reduce the effect of measurement noise and increase the accuracy of estimation process. Finally, the simulation results are presented to demonstrate the effectiveness of the proposed estimation method.

Full Text:



B. Barshan et al, “Evaluation of a Solid-State Gyroscope for Robotic Application,” IEEE Trans. On Instrumentation and Measurement, Vol. 44, No. 1(1994), pp. 61-67.

B. Barshan et al, “Inertial Navigation System for Mobile Robots,” IEEE Trans. Robot. Automat., Vol. 11, No. 3(1995), pp. 328-342.

P. Bristeau et al, “Trajectory estimation for a hybrid rocket,” AIAA Guidance Navigration and Control Conference, Chicago, US 2009.

B. Barshan et al, “Using data fusion of DMARS-R-IMU and GPS data for improving attitude determination accuracy,” Space Ops Conferences, 2016, Korea.

P. Tomé et al, “Integrating Multiple GPS Receivers With A Low Cost IMU For Aircraft Attitude Determination,” ION 1999 National Technical Meeting, Jan. 1999.

T. S. Bruggemann et al, “GPS Fault Detection with IMU and Aircraft Dynamics,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 47, No. 1 (2011), pp. 305-316.

F. Qin et al, “Performance assessment of a low-cost inertial measurement unit based ultra-tight global navigation satellite system/inertial navigation system integration for high dynamic applications,” IET Radar, Sonar Navigat., vol. 8, no. 7 (2014), pp.


A. Golovan et al, “Small satellite attitude determination based on GPS/IMU data fusion,” ICNPAA 2014: 10th International Conference on Mathematical Problems in Engineering Aerospace and Sciences AlP Conference Proceedings, Vol. 1637 (2014), pp. 341-348.

R. G. Brown et al, “Introduction to Random Signals and Applied Kalman Filtering,” 1997, John Wiley & Sons.

H. Rehbinder et al, “Drift-free attitude estimation for accelerated rigid bodies” Science Direct - Automatica, April, Vol. 40, No. 4 (2004), pp. 653.


Indexed by: Google Scholar.

Lớp dạy vẽ ở Mỹ Đình