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Detection of Bias in GPS satellites- Measurements for Enhanced Measurement Integrity

Authors: Mamoun F. Abdel-Hafez


In this paper, the detection of a fault in the Global Positioning System (GPS) measurement is addressed. The class of faults considered is a bias in the GPS pseudorange measurements. This bias is modeled as an unknown constant. The fault could be the result of a receiver fault or signal fault such as multipath error. A bias bank is constructed based on set of possible fault hypotheses. Initially, there is equal probability of occurrence for any of the biases in the bank. Subsequently, as the measurements are processed, the probability of occurrence for each of the biases is sequentially updated. The fault with a probability approaching unity will be declared as the current fault in the GPS measurement. The residual formed from the GPS and Inertial Measurement Unit (IMU) measurements is used to update the probability of each fault. Results will be presented to show the performance of the presented algorithm.

Keywords: Estimation and filtering, Statistical data analysis, Faultdetection and identification.

Digital Object Identifier (DOI):

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[1] P. S. Maybeck, Stochastic Models, Estimation and Control, Volume 1, Navtech Book and Software Store, Arlington, VA, 1994.
[2] B. Hofmann-Wellenhof, H. Lichtenegger, and J. Collins, GPS Theory and Practice, 4th Ed., Springer-Verlag/Wien, New York, 1997.
[3] B. W. Parkinson and J. J. Spiker, Global Positioning System: Theory and Applications, Vol. 1 and 2, American Institute of Aeronautics and Astronautics, Inc., Washington D.C., 1996.
[4] J. A. Farrel and M. Barth, The Global Positioning System and Inertial Navigation, McGraw Hill, San Francisco, 1999.
[5] B. J. Odelson, M. R. Rajamani, and J. B. Rawlings, A new Autocovariance Least-Squares Method for Estimating Noise Covariances, Automatica, no. 42, no. 3, pp. 303-308, 2005.
[6] B. J. Odelson, A. Lutz, and J. B. Rawlings, The Autocovariance Least- Squares Method for Estimating Covariances: Applications to Model- Based Control of Chemical Reactors, IEEE Transactions on Control Systems Technology, Vol. 14, No. 3, pp. 532-540, 2006.
[7] N. A. White, P. S. Maybeck, and S. L. DeVilbiss, Detection of Interference/ Jamming and Spoofing in a DGPS-Aided Inertial System, IEEE Transactions on Aerospace and Electronic Systems, Vol. 34, No. 4, pp. 1208-1217, 1998.
[8] M. Wei and K. P. Schwarz, A strapdown inertial algorithm using an Earth-fixed Cartesian frame, Navigation, Journal of the Institute of Navigation, Vol. 37, No. 2, pp. 153-167, 1990.
[9] S. Hong, M. Lee, J. Rios, and J. L. Speyer, Observability Analysis of GPS Aided INS, Proceedings of the 2000 Institute of Navigation, Salt Lake City, UT, Sept. 2000.
[10] W.R. Williamson, M.F. Abdel-Hafez, I. Ree, E. Song, J. Wolfe, D. Cooper, and J. L. Speyer, An Instrumentation System Applied to Formation Flight, IEEE Transactions on Control Systems Technology, vol. 15, No. 1, pp. 75-85, 2007.
[11] I. Rhee, M.F. Abdel-Hafez, and J.L. Speyer, On the Observability of Strapdown INS System During Maneuvers, IEEE Transactions on Aerospace and Electronic Systems, Vol. 40, No. 2, pp. 526-536, 2004.