GPS Signal Offset Detection and Noise Strength Estimation in a Parallel Kalman Filter Algorithm

Barry J. Vanek, Peter S. Maybeck, John F. Raquet

Abstract:	Measurements from Global Positioning System (GPS) satellites are subject to corruption by signal interference and induced offsets. This paper.presents two in~aepenuent algorithms to ensure the nawgat~on system remains uncorrupted by these possible GPS failures. The first is parameter estimation al.gorithm that estimates the measurement noise variance of each satellite. A redundant measurement differencing (RMD) technique provides direct observability of the aifferenced white measurement noise samples. The variance of the noise process is estimated and provided to the second algorithm, a parallel Kalman filter, which then adapts to changes in the real-world measurement noise strength. The parallel Kalman filter structure detects and isolates signal offsets in individual GPS satellites. The offset detection algorithm calculates test statistics on each of the filters and decides which satellites to use in the solu.tion based on these statistics. The two algorithms contam several user-definedparameters thathave significant effects when adjusted. The various effects of parameter variation are described and a parameter set is chosen at which to evaluate the algorithms. The comb.ined.. algorithm performs quite well in computer simulations.
Published in:	Proceedings of the 12th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 1999) September 14 - 17, 1999 Nashville, TN
Pages:	2243 - 2252
Cite this article:	Vanek, Barry J., Maybeck, Peter S., Raquet, John F., "GPS Signal Offset Detection and Noise Strength Estimation in a Parallel Kalman Filter Algorithm," Proceedings of the 12th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 1999), Nashville, TN, September 1999, pp. 2243-2252.
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