Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81562
Title: Tightly coupled GNSS/INS integration via factor graph and aided by fish-eye camera
Authors: Wen, W 
Bai, X 
Kan, YC 
Hsu, LT 
Keywords: GNSS
INS
Camera
Integration
Factor graph
Positioning
Autonomous driving
Issue Date: Nov-2019
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on vehicular technology, Nov. 2019, v. 68, no. 11, p. 10651-10662 How to cite?
Journal: IEEE transactions on vehicular technology 
Abstract: GNSS/INS integrated solution has been extensively studied over the past decades. However, its performance relies heavily on environmental conditions and sensor costs. The GNSS positioning can obtain satisfactory performance in the open area. Unfortunately, its accuracy can be severely degraded in a highly urbanized area, due to the notorious multipath effects and noneline-of-sight (NLOS) receptions. As a result, excessive GNSS outliers occur, which causes a huge error in GNSS/INS integration. This paper proposes to apply a fish-eye camera to capture the sky view image to further classify the NLOS and line-of-sight (LOS) measurements.Inaddition,therawINSandGNSSmeasurements are tightly integrated using a state-of-the-art probabilistic factor graphmodel.InsteadofexcludingtheNLOSreceptions,thispaper makes use of both the NLOS and LOS measurements by treating them with different weightings. Experiments conducted in typical urban canyons of Hong Kong showed that the proposed method could effectively mitigate the effects of GNSS outliers, and an improved accuracy of GNSS/INS integration was obtained, when compared with the conventional GNSS/INS integration.
URI: http://hdl.handle.net/10397/81562
ISSN: 0018-9545
EISSN: 1939-9359
DOI: 10.1109/TVT.2019.2944680
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