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Title: Extending shadow matching to tightly-coupled GNSS/INS integration system
Authors: Zhang, G 
Wen, W 
Xu, B 
Hsu, LT 
Issue Date: May-2020
Source: IEEE transactions on vehicular technology, May 2020, v. 69, no. 5, p. 4979 - 4991.
Abstract: Performing precise positioning is still challenging for autonomous driving. Global navigation satellite system (GNSS) performance can be significantly degraded due to the non-line-of-sight (NLOS) reception. Recently, the studies of 3D building model aided (3DMA) GNSS positioning show promising positioning improvements in urban canyons. In this study, the benefits of 3DMA GNSS are further extended to the GNSS/inertial navigation system (INS) integration system. Based on the shadow matching solution and scoring information of candidate positions, two methods are proposed to better classify the line-of-sight (LOS) and NLOS satellite measurements. Aided by the satellite visibility information, the NLOS-induced pseudorange measurement error can be mitigated before fusing GNSS with the INS in the loosely-coupled or tightly-coupled integration system. Both the proposed satellite visibility estimation methods achieve over 80% LOS/NLOS classification accuracy for most of the scenarios in the urban area, which are at least 10% improvement over the carrier-to-noise ratio ($C/{N_0}$)-based method. By further extending the satellite visibility estimation to exclude NLOS measurements and adjust the measurement noise covariance, the proposed 3DMA GNSS/INS tightly-coupled integrated positioning achieves nearly a factor of 3 improvements comparing to the conventional GNSS/INS integration method during the vehicular experiment in the urban canyon.
Keywords: 3D building model
Sensor integration
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE transactions on vehicular technology 
ISSN: 0018-9545
EISSN: 1939-9359
DOI: 10.1109/TVT.2020.2981093
Rights: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
The following publication Zhang, G., Wen, W., Xu, B., & Hsu, L. T. (2020). Extending shadow matching to tightly-coupled GNSS/INS integration system. IEEE Transactions on Vehicular Technology, 69(5), 4979-4991 is available at
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