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Predictive Attitude Estimation Using Global Positioning System SignalsIn this paper, a new algorithm is developed for attitude estimation using Global Positioning System (GPS) signals. The new algorithm is based on a predictive filtering scheme designed for spacecraft without rate measuring devices. The major advantage of this new algorithm over traditional Kalman filter approaches is that the model error is not assumed to represented by an unbiased Gaussian noise process with known covariance, but instead is determined during the estimation process. This is achieved by simultaneously solving system optimality conditions and an output error constraint. This approach is well suited for GPS attitude estimation since some error sources that contribute to attitude inaccuracy, such as signal multipath, are known to be non-Gaussian processes. Also, the predictive filter scheme can use either GPS signals or vector observations or a combination of both for attitude estimation, so that performance characteristics can be maintained during periods of GPS attitude sensor outage. The performance of the new algorithm is tested using flight data from the REX-2 spacecraft. Results are shown using the predictive filter to estimate the attitude from both GPS signals and magnetometer measurements, and comparing that solution to a magnetometer-only based solution. Results using the new estimation algorithm indicate that GPS-based solutions are verified to within 2 degrees using the magnetometer cross-check for the REX-2 spacecraft. GPS attitude accuracy of better than 1 degree is expected per axis, but cannot be reliably proven due to inaccuracies in the magnetic field model.
Document ID
19970017194
Document Type
Conference Paper
Authors
Crassidis, John L.
(Catholic Univ. of America Washington, DC United States)
Markley, F. Landis
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Lightsey, E. Glenn
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Ketchum, Eleanor
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Date Acquired
September 8, 2013
Publication Date
May 1, 1997
Publication Information
Publication: Flight Mechanics Symposium 1997
Subject Category
Astrodynamics
Accession Number
97N19554
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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