Stochastic Modeling for Static GPS Baseline Data Processing
- 1 November 1998
- journal article
- Published by American Society of Civil Engineers (ASCE) in Journal of Surveying Engineering
- Vol. 124 (4), 171-181
- https://doi.org/10.1061/(asce)0733-9453(1998)124:4(171)
Abstract
In global positioning system (GPS) data processing, incorrect stochastic models for double-differenced measurements will result in unreliable statistics for ambiguity search and biased positioning results. In the commonly used stochastic model, it is usually assumed that all the raw GPS measurements are independent and that they have the same variance. In fact, these assumptions are not realistic. Measurements obtained from different satellites cannot have the same accuracy due to varying noise levels. In this paper, a new method based on modern statistical theory is proposed to directly estimate the covariance matrix for double-differenced GPS measurements. Three different stochastic models have been tested and analyzed. Test results indicate that by using the proposed stochastic models the volume of ambiguity search space can be reduced and the reliability of the ambiguity resolution is improved. Also, the statistics of the baseline components estimated with the proposed stochastic models are more effic...Keywords
This publication has 10 references indexed in Scilit:
- Precise positioning with the GPSPublished by Springer Science and Business Media LLC ,2005
- A canonical theory for short GPS baselines. Part IV: precision versus reliabilityJournal of Geodesy, 1997
- Quality-control issues relating to instantaneous ambiguity resolution for real-time GPS kinematic positioningJournal of Geodesy, 1997
- Variance-covariance estimation of GPS NetworksJournal of Geodesy, 1994
- Variance component estimation applied to satellite laser rangingJournal of Geodesy, 1992
- On optimal filtering of GPS dual frequency observations without using orbit informationJournal of Geodesy, 1991
- Parameter Estimation and Hypothesis Testing in Linear ModelsPublished by Springer Science and Business Media LLC ,1988
- The inefficiency of least squaresBiometrika, 1975
- Estimation of variance and covariance components—MINQUE theoryJournal of Multivariate Analysis, 1971
- Estimation of Heteroscedastic Variances in Linear ModelsJournal of the American Statistical Association, 1970