MyJournals Home  

RSS FeedsRemote Sensing, Vol. 14, Pages 5975: Visual/Inertial/GNSS Integrated Navigation System under GNSS Spoofing Attack (Remote Sensing)

 
 

25 november 2022 14:24:51

 
Remote Sensing, Vol. 14, Pages 5975: Visual/Inertial/GNSS Integrated Navigation System under GNSS Spoofing Attack (Remote Sensing)
 


Visual/Inertial/GNSS (VIG) integrated navigation and positioning systems are widely used in unmanned vehicles and other systems. This VIG system is vulnerable to of GNSS spoofing attacks. Relevant research on the harm that spoofing causes to the system and performance analyses of VIG systems under GNSS spoofing are not sufficient. In this paper, an open-source VIG algorithm, VINS-Fusion, based on nonlinear optimization, is used to analyze the performance of the VIG system under a GNSS spoofing attack. The influence of the visual inertial odometer (VIO) scale estimation error and the transformation matrix deviation in the transition period of spoofing detection is analyzed. Deviation correction methods based on the GNSS-assisted scale compensation coefficient estimation method and optimal pose transformation matrix selection are proposed for VIG-integrated system in spoofing areas. For an area that the integrated system can revisit many times, a global pose map-matching method is proposed. An outfield experiment with a GNSS spoofing attack is carried out in this paper. The experiment result shows that, even if the GNSS measurements are seriously affected by the spoofing, the integrated system still can run independently, following the preset waypoint. The scale compensation coefficient estimation method, the optimal pose transformation matrix selection method and the global pose map-matching method can depress the estimation error under the circumstances of a spoofing attack.


 
136 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 14, Pages 5976: Two-Step Matching Method Based on Co-Occurrence Scale Space Combined with Second-Order Gaussian Steerable Filter (Remote Sensing)
Remote Sensing, Vol. 14, Pages 5977: Gaussian Process Modeling of In-Season Physiological Parameters of Spring Wheat Based on Airborne Imagery from Two Hyperspectral Cameras and Apparent Soil Electrical Conductivity (Remote Sensing)
 
 
blog comments powered by Disqus


MyJournals.org
The latest issues of all your favorite science journals on one page

Username:
Password:

Register | Retrieve

Search:

Physics


Copyright © 2008 - 2024 Indigonet Services B.V.. Contact: Tim Hulsen. Read here our privacy notice.
Other websites of Indigonet Services B.V.: Nieuws Vacatures News Tweets Nachrichten