Title: GNSS Multipath Detection in Urban Environment Using 3D Building Model
Author(s): Shiwen Zhang, Sherman Lo, Yu-Hsuan Chen, Todd Walter, Per Enge
Published in: Proceedings of IEEE/ION PLANS 2018
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 1053 - 1058
Cite this article: Zhang, Shiwen, Lo, Sherman, Chen, Yu-Hsuan, Walter, Todd, Enge, Per, "GNSS Multipath Detection in Urban Environment Using 3D Building Model," Proceedings of IEEE/ION PLANS 2018, Monterey, CA, April 2018, pp. 1053-1058.
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Abstract: The paper describes a multipath detection algorithm to predict and exclude multipath signals using a raytracing algorithm on a three-dimensional building model. In addition, a sensitivity analysis was performed to estimate the confidence level of the model’s multipath prediction. A field test was performed and experimental results showed that the detection accuracy using a building model is sensitive to both the modeling uncertainty and the accuracy of the initial user position estimate. Position accuracy was improved after applying the proposed detection algorithm.