Estimation of the Stochastic Model for Long-Baseline Kinematic GPS Applications

Donghyun Kim and Richard B. Langley

Abstract:	We propose a new approach for the stochastic model for long-baseline kinematic GPS positioning which can be derived directly from the observation time series under a simple assumption. The performance of our approach was compared with those of existing approaches for the stochastic model Πthe elevation-angle dependent function approach, the signal-to-noise ratio or alternatively the carrier-to-noise-power-density ratio approach, and the least-squares adaptation approach. These alternative approaches may have significant limitations in some applications: First, the elevation-angle dependent function is not advisable in kinematic situations because the relationship between antenna gain and the signal elevation angle may be difficult to assess when the antenna orientation is changing which can happen often in kinematic situations. Second, although some GPS receiver manufacturers provide SNR-like values in their data streams, easily-interpreted SNR values are not easy to come by. Third, the least-squares adaptation approach is not advisable for the long-baseline kinematic applications because it is difficult to obtain surplus redundancy in such applications. Our new approach is free of these difficulties. Although initially developed for long-baseline kinematic applications, it can be used for all situations whether short-baseline or long-baseline, static or kinematic, and for either real-time or post-processing needs.
Published in:	Proceedings of the 2001 National Technical Meeting of The Institute of Navigation January 22 - 24, 2001 Westin Long Beach Hotel Long Beach, CA
Pages:	586 - 595
Cite this article:	Kim, Donghyun, Langley, Richard B., "Estimation of the Stochastic Model for Long-Baseline Kinematic GPS Applications," Proceedings of the 2001 National Technical Meeting of The Institute of Navigation, Long Beach, CA, January 2001, pp. 586-595.
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