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Map-aided integrity monitoring of a land vehicle navigation system

journal contribution
posted on 30.07.2013, 14:11 by Nagendra R. Velaga, Mohammed Quddus, Abigail Bristow, Yuheng Zheng
The concept of user-level integrity monitoring has been successfully applied to air transport navigation systems, where the main focus is on the errors associated with the Global Positioning System (GPS)-data-processing chain. Little research effort has been devoted to the study of integrity monitoring for the case of land vehicle navigation systems. The primary difference is that it is also necessary to consider errors associated with a spatial map and a map-matching (MM) process when monitoring the integrity of a land vehicle navigation system. This is because these two components play a vital role in land vehicle navigation. To date, research has focused on either the integrity of raw positioning data obtained from GPS or the integrity of the MM process and digital map errors. In this paper, these sources of error are simultaneously considered. Therefore, the main contribution of this paper is to report the development of a user-level integrity-monitoring system that concurrently takes into account all the potential error sources associated with a navigation system and considers the operational environment to further improve performance. Errors associated with a spatial road map are given special attention. Two knowledge-based fuzzy inference systems were developed to measure the integrity scale. The performance of the integrity method was assessed using field data collected in Nottingham and London, U.K. The results indicate that the integrity method provides valid warnings 98.2% and 99.4% of the time for positioning data in a mixed operational environment in Nottingham and suburban areas of London, respectively.



  • Architecture, Building and Civil Engineering


VELAGA, N.R. ... et al., 2012. Map-aided integrity monitoring of a land vehicle navigation system. IEEE Transactions on Intelligent Transportation Systems, 13 (2), pp. 848 - 858.




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Closed Access. This article was published in the journal, IEEE Transactions on Intelligent Transportation Systems [© IEEE].






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