Comparison of Interpolation Algorithms in Network-Based GPS Techniques

Liwen Dai, Shaowei Han, Jinling Wang, and Chris Rizos

Peer Reviewed

Abstract: This paper compares the interpolation methods used in network-based GPS techniques, including the linear combination model, distance-based linear interpolation method, linear interpolation method, lowerorder surface model, and least-squares collocation. The advantages and disadvantages of each method are discussed. All of the methods use an n – 1 independent error vector generated from a network of n reference stations to model the distance-dependent biases at the user station. General formulas for all of the methods involve first computation of the n – 1 coefficients, and then formation of an n – 1 linear combination with an n – 1 error vector from the reference stations to mitigate the spatially correlated errors for the user station(s). Test results from multiple reference stations show that all of the methods can significantly reduce the distance-dependent biases at the GPS user station. The performance of all the methods is comparable.
Published in: NAVIGATION: Journal of the Institute of Navigation, Volume 50, Number 4
Pages: 277 - 293
Cite this article: Dai, Liwen, Han, Shaowei, Wang, Jinling, Rizos, Chris, "Comparison of Interpolation Algorithms in Network-Based GPS Techniques", NAVIGATION: Journal of The Institute of Navigation, Vol. 50, No. 4, Winter 2003-2004, pp. 277-293.
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