Abstract
Recently an unmanned aerial vehicle (UAV) has been widely used for military and civil applications. The role of a navigation system in the UAV is to provide navigation data to the flight control computer (FCC) for guidance and control. Since performance of the FCC is highly reliant on the navigation data, a fault in the navigation system may lead to a disastrous failure of the whole UAV. Therefore, the navigation system should possess a fault detection and isolation (FDI) algorithm. This paper proposes an attitude determination GPS/INS integrated navigation system with an FDI algorithm for a UAV. Hardware for the proposed navigation system has been developed. The developed hardware comprises a commercial inertial measurement unit (IMU) and the integrated navigation package (INP) which includes an attitude determination GPS (ADGPS) receiver and a navigation computer unit (NCU). The navigation algorithm was implemented in a real-time operating system with a multi-tasking structure. To evaluate performance of the proposed navigation system, a flight test has been performed using a small aircraft. The test results show that the proposed navigation system can give accurate navigation results even in a high dynamic environment.
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Abbreviations
- Hk :
-
Measurement matrix at time tk
- lk :
-
Test statistic at time tk
- N :
-
Window size
- N(μ, σ2):
-
Normal distribution with mean μ and variance σ2
- p :
-
Dimension of the residual vector γk
- P k :
-
Error covariance matrix al timet k
- Q k :
-
Covariance matrix of the process noise at timet k
- R k :
-
Covariance matrix of the measurement noise at timet k
- V k :
-
Covaviancc matrix of the residual vectorY k at timet k
- X k :
-
State vector at timeY k
- Z k :
-
Measurement vector at timeY k
- X 2 n :
-
Chi-square distribution withn degree-of-freedom
- ε:
-
Decision threshold
- γ k :
-
Residual vector at timet k
References
Blakelock J. H., 1991,Automatic Control of Aircraft and Missiles, 2nd edition, John Wiley & Sons, New York.
Brenner, M., 1995, “Integrated GPS/Inertial Fault Detection Availability,”Proceedings of the ION GPS-95, pp. 1949–1958.
Brumback, B. D. and Srinath, M. D., 1987, “A Chi-Square Test for Fault-Detection in Kalman Filters,”IEEE Transactions on Automatic Control, Vol. AC-32, No. 6, pp. 552–554.
Cox, D. B., 1980, “Integration of GPS with Inertial Navigation Systems,” reprinted inCollected GPS Papers, Vol. I, pp. 144–153, Institute of Navigation, Alexandria, VA.
Da, R., 1994, “Failure Detection of Dynamical Systems with the State Chi-Square Test,”Journal of Guidance, Control, and Dynamics, Vol. 17, No. 2, pp. 271–277.
Diesel, J. and King, J., 1995, “Integration of Navigation System for Fault Detection, Exclusion, and Integrity Determination-Without WASS,”Proceedings of the ION GPS-95, pp. 683–692.
Gautier, J. D. and Parkinson, B. W., 2003, “Using the GPS/INS Generalized Evaluation Tool (GIGET) for the Comparison of Loosely Coupled, Tightly Coupled and Ultra-Tightly Coupled Integrated Navigation Systems,”Proceedings of the ION 59th Annual Meeting, pp. 65–76.
Gebre-Egziabher, D., Hayward, D. R. and Powell, C. D., 1998, “A Low-Cost GPS/lnertial Attitude Heading Reference System (AHRS) for General Aviation Applications,”Proceedings of the Position Location and Navigation Symposium, pp. 518–525.
Grewal, M. S., Weill, L. R. and Andrews, A. P., 2001,Global Positioning Systems, Inertial Navigation, and Integration, John Wiley & Sons, New York.
Hong, S. P., Lee, M. H., Rios, J. A. and Speyer, J. L., 2002, “Observability Analysis of INS with a GPS Multi-Antenna System,”KSME International Journal, Vol. 16, No. 11, pp. 1367–1378.
Mathes, S., Herberg, J. and Berking, B., 2003, “Functional Scope and Generic Model of Integrated Navigation Systems,”The Journal of Navigation, Vol. 56, pp. 153–175.
May beck, P. S., 1979,Stochastic Models, Estimation and Control, Vol. 1, Academic Press, New York.
McMillan, J. C, 1994, “Sensor Integration Options for Low Cost Position & Attitude Determination,”Proceedings of the Position Location and Navigation Symposium, pp. 453–459.
Michael A., 1988,Unmanned Aircraft (Brassey’s Air Power: Aircraft, Weapon Systems and Technology series, vol. 3, Brassey's Defence Publishers, London.
Newport, J. R., 1994,Avionic Systems Design, CRC Press, Boca Ration.
Oh, S. H., Hwang, D. -H. and Lee, S. J., 2001, “An Efficient Integration Scheme for the INS and the Attitude Determination GPS Receiver,”Proceedings of the ION 57th Annual Meeting, pp. 334–340.
Rios, J. A. and White, E., 2001, “Fusion Filter Algorithm Enhancements for a MEMS GPS/ IMU,”Proceedings of the ION GPS 2001, pp. 1382–1393.
Satz, H. S., Cox, D. B., Beard, R. L. and Landis, G. P., 1991, “GPS Inertial Attitude Estimation via Carrier Accumulated-phase Measurements,”Journal of the Institute of Navigation, Vol. 38, No. 3, pp. 273–284.
Sukkarieh, S., Nebot, E. M. and Durrant-Whyte, H. F., 1999, “A High Integrity IMU/GPS Navigation Loop for Autonomous Land Vehicle Applications,”IEEE Transactions on Robotics and Automation, Vol. 15, No. 3, pp. 572–578.
Tsach, S., Penn, D. and Levy, A., 2002, “Advanced Technologies and Approaches for Next Generation UAVs,”Proceedings of ICAS 2002 Congress, pp. 131.1-131.10.
Titterton, D. H. and Weston, J. L., 1997,Strapdown Inertial Navigation Technology, Peter Peregrinus Ltd., London, UK.
Wolf, R., Hein, G. W., Eissfeller, B. and Loehnert, E., 1996, “An Integrated Low Cost GPS/INS Attitude Determination and Position Location System,”Proceedings of the ION GPS 96, pp. 975–981.
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Oh, S.H., Hwang, DH., Park, C. et al. Attitude determination GPS/INS integrated navigation system with FDI algorithm for a UAV. J Mech Sci Technol 19, 1529–1543 (2005). https://doi.org/10.1007/BF03023931
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DOI: https://doi.org/10.1007/BF03023931