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A Unified Framework for GPS Code and Carrier-Phase Multipath Mitigation Using Support Vector Regression

Phan, Huy, Tan, Su-Lim, McLoughlin, Ian Vince, Vu, Duc-Lung Vu (2013) A Unified Framework for GPS Code and Carrier-Phase Multipath Mitigation Using Support Vector Regression. Advances in Artificial Neural Systems, 2013 . p. 240564. ISSN 1687-7594. (doi:10.1155/2013/240564) (KAR id:48895)


Multipath mitigation is a long-standing problem in global positioning system (GPS) research and is essential for improving the accuracy and precision of positioning solutions. In this work, we consider multipath error estimation as a regression problem and propose a unified framework for both code and carrier-phase multipath mitigation for ground fixed GPS stations. We use the kernel support vector machine to predict multipath errors, since it is known to potentially offer better-performance traditional models, such as neural networks. The predicted multipath error is then used to correct GPS measurements. We empirically show that the proposed method can reduce the code multipath error standard deviation up to 79% on average, which significantly outperforms other approaches in the literature. A comparative analysis of reduction of double-differential carrier-phase multipath error reveals that a 57% reduction is also achieved. Furthermore, by simulation, we also show that this method is robust to coexisting signals of phenomena (e.g., seismic signals) we wish to preserve.

Item Type: Article
DOI/Identification number: 10.1155/2013/240564
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Ian McLoughlin
Date Deposited: 25 Aug 2015 09:51 UTC
Last Modified: 09 Dec 2022 07:28 UTC
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Phan, Huy:
McLoughlin, Ian Vince:
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